BACKGROUND/OBJECTIVES

White matter hyperintensities (WMH) and silent brain infarcts (SBI) have been associated with both vascular factors and cognitive decline. We examined among cognitively normal elderly, whether vascular factors predict cognitive decline and whether these associations are mediated by MRI measures of subclinical vascular brain injury.

DESIGN

Prospective multi-site longitudinal study of subcortical ischemic vascular diseases

SETTING

Memory and aging centers in California

PARTICIPANTS

We studied 74 participants who were cognitively normal at entry and received at least 2 neuropsychological evaluations and 2 MRI exams over an average follow-up of 6.9 years.

MEASUREMENTS

Item response theory was used to create composite scores of global, verbal memory, and executive functioning. Volumetric MRI measures included WMH, SBI, hippocampus, and cortical gray matter (CGM). We used linear mixed effects models to examine the associations between vascular factors, MRI measures, and cognitive scores.

RESULTS

History of coronary artery disease (CAD) was associated with greater declines in global, verbal memory, and executive cognition. The CAD associations remained after controlling for changes in WMH, SBI, hippocampal and CGM volumes.

CONCLUSION

History of CAD may be a surrogate marker for clinically significant atherosclerosis which also affects the brain. Structural MRI measures of WMH and SBI do not fully capture the potential adverse effects of atherosclerosis on the brain. Future longitudinal studies of cognition should incorporate direct measures of atherosclerosis in cerebral arteries, as well as more sensitive neuroimaging measures.

Magnetic Resonance Imaging (MRI) provides various imaging modes to study the brain. We tested the benefits of a joint analysis of multimodality MRI data in combination with a large-scale analysis that involved simultaneously all image voxels using joint independent components analysis (jICA) and compared the outcome to results using conventional voxel-by-voxel unimodality tests. Specifically, we designed a jICA to decompose multimodality MRI data into independent components that explain joint variations between the image modalities as well as variations across brain regions. We tested the jICA design on structural and perfusion-weighted MRI data from 12 patients diagnosed with behavioral variant frontotemporal dementia (bvFTD) and 12 cognitively normal elderly individuals. While unimodality analyses showed widespread brain atrophy and hypoperfusion in the patients, jICA further revealed two significant joint components of variations between atrophy and hypoperfusion across brain regions. The 1st joint component revealed associated brain atrophy and hypoperfusion predominantly in the right brain hemisphere in behavioral variant frontotemporal dementia, and the 2nd joint component revealed greater atrophy relative to hypoperfusion affecting predominantly the left hemisphere in behavioral variant frontotemporal dementia. The patterns are consistent with the clinical symptoms of behavioral variant frontotemporal dementia that relate to asymmetric compromises of the left and right brain hemispheres. The joint components also revealed that that structural alterations can be associated with physiological alterations in spatially separated but potentially connected brain regions. Finally, jICA outperformed voxel-by-voxel unimodal tests significantly in terms of an effect size, separating the behavioral variant frontotemporal dementia patients from the controls. Taken together, the results demonstrate the benefit of multimodality MRI in conjunction with jICA for mapping neurodegeneration, which may lead ultimately to an improved diagnosis of behavioral variant frontotemporal dementia and other forms of neurodegenerative diseases.

The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic and biochemical biomarkers for the early detection and tracking of Alzheimer’s disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD and 200 normal controls and $67 million funding was provided by both the public and private sectors including the National Institutes on Aging, thirteen pharmaceutical companies and two Foundations that provided support through the Foundation for NIH (FNIH). This article reviews all papers published since the inception of the initiative and summarizes the results as of February, 2011. The major accomplishments of ADNI have been 1) the development of standardized methods for clinical, magnetic resonance imaging (MRI) and positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarkers in a multi-center setting; 2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control, MCI and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β amyloid (Aβ) cascade [1] and tau mediated neurodegeneration hypotheses for AD while brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; 3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities including MRI, FDG-PET, CSF biomarkers and clinical tests; 4) the development of methods for the early detection of AD. CSF biomarkers, Aβ42 and tau as well as amyloid PET may reflect the earliest steps in AD pathology in mildly or even non-symptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; 5) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Baseline cognitive and/or MRI measures generally predicted future decline better than other modalities whereas MRI measures of change were shown to be the most efficient outcome measures; 6) the confirmation of the AD risk loci CLU, CR1 and PICALM and the identification of novel candidate risk loci; 7) worldwide impact through the establishment of ADNI-like programs in Europe, Asia and Australia; 8) understanding the biology and pathobiology of normal aging, MCI and AD through integration of ADNI biomarker data with clinical data from ADNI to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD thereby advancing efforts to find disease modifying drugs for AD; and 9) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world. The ADNI study was extended by a two year Grand Opportunities grant in 2009 and a renewal of ADNI (ADNI2) in October, 2010 through to 2016, with enrollment of an additional 550 participants.

Penalized or sparse regression methods are gaining increasing attention in imaging genomics, as they can select optimal regressors from a large set of predictors whose individual effects are small or mostly zero. We applied a multivariate approach, based on L1-L2-regularized regression (elastic net) to predict a magnetic resonance imaging (MRI) tensor-based morphometry-derived measure of temporal lobe volume from a genome-wide scan in 740 Alzheimer’s Disease Neuroimaging Initiative (ADNI) subjects. We tuned the elastic net model’s parameters using internal crossvalidation and evaluated the model on independent test sets. Compared to 100,000 permutations performed with randomized imaging measures, the predictions were found to be statistically significant (p ~ 0.001). The rs9933137 variant in the RBFOX1 gene was a highly contributory genotype, along with rs10845840 in GRIN2B and rs2456930, discovered previously in a univariate genomewide search.

Alzheimer’s Disease (AD) has long been considered a cortical degenerative disease, but impaired brain connectivity, due to white matter injury, may exacerbate cognitive problems. Predicting brain changes is critically important for early treatment. In a longitudinal diffusion tensor imaging study, we investigated white matter fiber integrity in 19 patients (mean age: 74.7 +/− 8.4 yrs at baseline) displaying early signs of mild cognitive impairment (eMCI). We first examined whether baseline average fractional anisotropy (FA) measures in the corpus callosum (CC) predicted changes in white matter integrity over the following 6 months. We then examined whether “small world” architecture measures - calculated from baseline connectivity maps - predicted white matter changes over the next 6 months. While average CC FA measures at baseline were not associated with future changes in FA, network measures were a sensitive biomarker for predicting white matter changes during this critical time before AD strikes.

Patients with corticobasal degeneration (CBD) pathology present with diverse clinical syndromes also associated with other neuropathologies, including corticobasal syndrome, progressive nonfluent aphasia, and an Alzheimer’s-type dementia. Some present with behavioral variant frontotemporal dementia (bvFTD), though this subtype still requires more detailed phenotypic characterization. All patients with CBD pathology and clinical assessment were reviewed (N=17) and selected if they initially met criteria for bvFTD [bvFTD(CBD): N=5]. Available bvFTD patients with Pick’s [bvFTD(Pick’s): N=5] were selected as controls. Patients were also compared to healthy older controls [N=53] on neuropsychological and neuroimaging measures. At initial presentation, bvFTD(CBD) showed few neuropsychological or motor differences from bvFTD(Pick’s). Neuropsychiatrically, they were predominantly apathetic with less florid social disinhibition and eating disturbances, and were more anxious than bvFTD(Pick’s) patients. Voxel-based morphometry revealed similar patterns of predominantly frontal atrophy between bvFTD groups, though overall degree of atrophy was less severe in bvFTD(CBD), who also showed comparative preservation of the frontoinsular rim, with dorsal > ventral frontal atrophy, and sparing of temporal and parietal structures relative to bvFTD(Pick’s) patients. Despite remarkable overlap between the two patient types, bvFTD patients with underlying CBD pathology show subtle clinical features that may distinguish them from patients with Pick’s disease neuropathology.

The goal of this study was to determine whether PTSD was associated with an increase in time-related decline in macrostructural brain volume and whether these changes were associated with accelerated cognitive decline. To quantify brain structure, 3 dimensional T1-weighted MRI scans were performed at baseline and again after a minimum of 24 months in 25 patients with PTSD and 22 controls. Longitudinal changes in brain volume were measured using deformation morphometry. For the group as a whole PTSD+ patients did not show significant ongoing brain atrophy compared to PTSD-. PTSD+ patients were then subgrouped into those with decreasing or increasing symptoms. We found little evidence for brain markers of accelerated atrophy in PTSD+ veterans whose symptoms improved over time, with only a small left parietal region showing greater ongoing tissue loss than PTSD-. PTSD patients whose symptoms increased over time showed accelerated atrophy throughout the brain, particularly brainstem and frontal and temporal lobes. Lastly, for the sample as a whole greater rates of brain atrophy were associated with greater rates of decline in verbal memory and delayed facial recognition.

Alzheimer’s disease (AD) is a progressive age-related neurodegenerative disease. At the time of clinical manifestation of dementia, significant irreversible brain damage is already present, rendering the diagnosis of AD at early stages of the disease an urgent prerequisite for therapeutic treatment to halt, or at least slow, disease progression. In this Review, we discuss various neuroimaging measures that are proving to have potential value as biomarkers of AD pathology for the detection and prediction of AD before the onset of dementia. Recent studies that have identified AD-like structural and functional brain changes in elderly people who are cognitively within the normal range or who have mild cognitive impairment (MCI) are discussed. A dynamic sequence model of changes that occur in neuroimaging markers during the different disease stages is presented and the predictive value of multimodal neuroimaging for AD dementia is considered.

The Functional Activities Questionnaire (FAQ) and Alzheimer’s Disease Assessment Scale – cognitive subscale (ADAS-cog) are frequently-used indices of cognitive decline in Alzheimer’s disease (AD). The goal of this study was to compare FDG-PET and clinical measurements in a large sample of elderly subjects with memory disturbance. We examined relationships between glucose metabolism in FDG-PET regions of interest (FDG-ROIs), and ADAS-cog and FAQ scores in AD and mild cognitive impairment (MCI) patients enrolled in the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Low glucose metabolism at baseline predicted subsequent ADAS-cog and FAQ decline. In addition, longitudinal glucose metabolism decline was associated with concurrent ADAS-cog and FAQ decline. Additionally, a power analysis revealed that FDG-ROI values have greater statistical power than ADAS-cog to detect attenuation of cognitive decline in AD and MCI patients. Glucose metabolism is a sensitive measure of change in cognition and functional ability in AD and MCI, and has value in predicting future cognitive decline.

Hippocampal sclerosis (HS) is a common and often asymmetric neuropathological finding among elderly persons who experience progressive memory loss, but its cause is unknown and it is rarely diagnosed during life. In order to improve both understanding and diagnosis of late-life HS, bilateral hippocampi and cerebral hemispheres were reviewed in 130 consecutive autopsy cases drawn from a longitudinal study of subjects with subcortical ischemic vascular dementia (IVD), Alzheimer disease (AD) and normal aging. HS was found in 31 of 130 cases (24.5%). Of these, 45% were bilateral, 32% left-sided, and 23% right-sided. The majority of HS cases involved the entire rostral-caudal extent of the hippocampus. However, in 7 cases HS was focal in nature and was only found at or anterior to the lateral geniculate nucleus. In 77% of cases, HS was accompanied by other types of pathology (‘mixed’ HS), but in 23% of cases it was the sole neuropathologic finding (‘pure’ HS). TDP-43-positive cytoplasmic inclusions were found in dentate granule cells in 93% of all HS cases, 55% of AD cases with no HS, but 0% of IVD cases with no HS. MRI hippocampal volumes were significantly lower in bilateral HS compared to AD (p < 0.001) and in unilateral HS cases compared to cases with intact hippocampi (p < 0.001). Since HS may occur unilaterally in approximately a quarter of cases, its prevalence may be underestimated if only one cerebral hemisphere is examined. The presence of TDP-43 inclusions in HS cases, regardless of accompanying pathologies (e.g., AD, IVD, FTLD), is consistent with an underlying neurodegenerative pathogenetic mechanism. Further studies are warranted to determine whether greater severity of hippocampal atrophy on MRI may assist the clinical differentiation of HS from AD.

Imaging traits provide a powerful and biologically relevant substrate to examine the influence of genetics on the brain. Interest in genome-wide, brain-wide search for influential genetic variants is growing, but has mainly focused on univariate, SNP-based association tests. Moving to gene-based multivariate statistics, we can test the combined effect of multiple genetic variants in a single test statistic. Multivariate models can reduce the number of statistical tests in gene-wide or genome-wide scans and may discover gene effects undetectable with SNP-based methods. Here we present a gene-based method for associating the joint effect of single nucleotide polymorphisms (SNPs) in 18,044 genes across 31,662 voxels of the whole brain in 731 elderly subjects (mean age: 75.56 ± 6.82SD years; 430 males) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Structural MRI scans were analyzed using tensor-based morphometry (TBM) to compute 3D maps of regional brain volume differences compared to an average template image based on healthy elderly subjects. Using the voxel-level volume difference values as the phenotype, we selected the most significantly associated gene (out of 18,044) at each voxel across the brain. No genes identified were significant after correction for multiple comparisons, but several known candidates were re-identified, as were other genes highly relevant to brain function. GAB2, which has been previously associated with late-onset AD, was identified as the top gene in this study, suggesting the validity of the approach. This multivariate, gene-based voxelwise association study offers a novel framework to detect genetic influences on the brain.

Elevated homocysteine levels are a known risk factor for Alzheimer’s disease and vascular disorders. Here we applied tensor-based morphometry to brain magnetic resonance imaging scans of 732 elderly individuals from the Alzheimer’s Disease Neuroimaging Initiative study, to determine associations between homocysteine and brain atrophy. Those with higher homocysteine levels showed greater frontal, parietal, and occipital white matter atrophy in the entire cohort, irrespective of diagnosis, age, or sex. This association was also found when considering mild cognitive impairment individuals separately. Vitamin B supplements, such as folate, may help prevent homocysteine-related atrophy in Alzheimer’s disease by possibly reducing homocysteine levels. These atrophy profiles may, in the future, offer a potential biomarker to gauge the efficacy of interventions using dietary folate supplementation.

Background

Histopathological studies and animal models suggest that hippocampal subfields may be differently affected by aging, Alzheimer’s disease (AD), and other diseases. High-resolution images at 4 Tesla depict details of the internal structure of the hippocampus allowing for in vivo volumetry of different subfields. The aims of this study were as follows: (1) to determine patterns of volume loss in hippocampal subfields in normal aging, AD, and amnestic mild cognitive impairment (MCI). (2) To determine if measurements of hippocampal subfields provide advantages over total hippocampal volume for differentiation between groups.

Methods

Ninety-one subjects (53 controls (mean age: 69.3 ± 7.3), 20 MCI (mean age: 73.6 ± 7.1), and 18 AD (mean age: 69.1 ± 9.5) were studied with a high-resolution T2 weighted imaging sequence aimed at the hippocampus. Entorhinal cortex (ERC), subiculum, CA1, CA1–CA2 transition zone (CA1-2), CA3 & dentate gyrus (CA3&DG) were manually marked in the anterior third of the hippocampal body. Hippocampal volume was obtained from the Freesurfer and manually edited.

Results

Compared to controls, AD had smaller volumes of ERC, subiculum, CA1, CA1-2, and total hippocampal volumes. MCI had smaller CA1-2 volumes. Discriminant analysis and power analysis showed that CA1-2 was superior to total hippocampal volume for distinction between controls and MCI.

Conclusion

The patterns of subfield atrophy in AD and MCI were consistent with patterns of neuronal cell loss/reduced synaptic density described by histopathology. These preliminary findings suggest that hippocampal subfield volumetry might be a better measure for diagnosis of early AD and for detection of other disease effects than measurement of total hippocampus.

Amyloid-β accumulation in the brain is thought to be one of the earliest events in Alzheimer’s disease, possibly leading to synaptic dysfunction, neurodegeneration and cognitive/functional decline. The earliest detectable changes seen with neuroimaging appear to be amyloid-β accumulation detected by 11C-labelled Pittsburgh compound B positron emission tomography imaging. However, some individuals tolerate high brain amyloid-β loads without developing symptoms, while others progressively decline, suggesting that events in the brain downstream from amyloid-β deposition, such as regional brain atrophy rates, play an important role. The main purpose of this study was to understand the relationship between the regional distributions of increased amyloid-β and the regional distribution of increased brain atrophy rates in patients with mild cognitive impairment. To simultaneously capture the spatial distributions of amyloid-β and brain atrophy rates, we employed the statistical concept of parallel independent component analysis, an effective method for joint analysis of multimodal imaging data. Parallel independent component analysis identified significant relationships between two patterns of amyloid-β deposition and atrophy rates: (i) increased amyloid-β burden in the left precuneus/cuneus and medial-temporal regions was associated with increased brain atrophy rates in the left medial-temporal and parietal regions; and (ii) in contrast, increased amyloid-β burden in bilateral precuneus/cuneus and parietal regions was associated with increased brain atrophy rates in the right medial temporal regions. The spatial distribution of increased amyloid-β and the associated spatial distribution of increased brain atrophy rates embrace a characteristic pattern of brain structures known for a high vulnerability to Alzheimer’s disease pathology, encouraging for the use of 11C-labelled Pittsburgh compound B positron emission tomography measures as early indicators of Alzheimer’s disease. These results may begin to shed light on the mechanisms by which amyloid-β deposition leads to neurodegeneration and cognitive decline and the development of a more specific Alzheimer’s disease-specific imaging signature for diagnosis and use of this knowledge in the development of new anti-therapies for Alzheimer’s disease.

The caudate is a subcortical brain structure implicated in many common neurological and psychiatric disorders. To identify specific genes associated with variations in caudate volume, structural MRI and genome-wide genotypes were acquired from two large cohorts, the Alzheimer’s Disease NeuroImaging Initiative (ADNI; N=734) and the Brisbane Adolescent/Young Adult Longitudinal Twin Study (BLTS; N=464). In a preliminary analysis of heritability, around 90% of the variation in caudate volume was due to genetic factors. We then conducted genome-wide association to find common variants that contribute to this relatively high heritability. Replicated genetic association was found for the right caudate volume at SNP rs163030 in the ADNI discovery sample (P=2.36×10−6) and in the BLTS replication sample (P=0.012). This genetic variation accounted for 2.79% and 1.61% of the trait variance, respectively. The peak of association was found in and around two genes, WDR41 and PDE8B, involved in dopamine signaling and development. In addition, a previously identified mutation in PDE8B causes a rare autosomal-dominant type of striatal degeneration. Searching across both samples offers a rigorous way to screen for genes consistently influencing brain structure at different stages of life. Variants identified here may be relevant to common disorders affecting the caudate.

Elderly patients who have an acute illness or who undergo surgery often experience cognitive decline. The pathophysiologic mechanisms that cause neurodegeneration resulting in cognitive decline, including protein deposition and neuroinflammation, also play a role in animal models of surgery-induced cognitive decline. With the aging of the population, surgical candidates of advanced age with underlying neurodegeneration are encountered more often, raising concerns that, in patients with this combination, cognitive function will precipitously decline postoperatively. This special article is based on a symposium that the University of California, San Francisco, convened to explore the contributions of surgery and anesthesia to the development of cognitive decline in the aged patient. A road map to further elucidate the mechanisms, diagnosis, risk factors, mitigation, and treatment of postoperative cognitive decline in the elderly is provided.

Background

PIB PET and CSF Aβ42 demonstrate a highly significant inverse correlation. Both are presumed to measure brain Aβ amyloid load. Our objectives were to develop a method to transform CSF Aβ42 measures into calculated PIB measures (PIBcalc) of Aβ amyloid load, and to partially validate the method in an independent sample of subjects.

Methods

Forty-one ADNI subjects underwent PIB PET imaging and lumbar puncture (LP) at the same time. This sample, referred to as the “training” sample (9 cognitively normal (CN), 22 MCI, and 10 AD), was used to develop a regression model by which CSF Aβ42 (with APOE ε4 genotype as a covariate) was transformed into units of PIB PET (PIBcalc). An independent “supporting” sample of 362 (105 CN, 164 MCI, 93AD) ADNI subjects who underwent LP but not PIB PET imaging had their CSF Aβ42 values converted to PIBcalc. These values were compared to the overall PIB PET distribution found in the ADNI subjects (n = 102).

Results

A linear regression model demonstrates good prediction of actual PIB PET from CSF Aβ42 measures obtained in the training sample (R2 = 0.77, P<0.001). PIBcalc data (derived from CSF Aβ42) in the supporting sample of 362 ADNI subjects who underwent LP but not PIB PET imaging demonstrates group-wise distributions that are highly consistent with the larger ADNI PIB PET distribution and with published PIB PET imaging studies.

Conclusion

Although the precise parameters of this model are specific for the ADNI sample, we conclude that CSF Aβ42 can be transformed into calculated PIB (PIBcalc) measures of Aβ amyloid load. Brain Aβ amyloid load can be ascertained at baseline in therapeutic or observational studies by either CSF or amyloid PET imaging and the data can be pooled using well-established multiple imputation techniques that account for the uncertainty in a CSF-based calculated PIB value.

A previous study (1) suggested that individuals with Gulf War Illness (GWI) had reduced quantities of the neuronal marker N-acetyl aspartate (NAA) in the basal ganglia and pons. This study aimed to determine whether NAA is reduced in these regions and to investigate correlations with other possible causes of GWI, such as psychological response to stress in a large cohort of Gulf war veterans. Individuals underwent tests to determine their physical and psychological health and to identify veterans with (n=81) and without (n=97) GWI. When concentrations of NAA and ratios of NAA to creatine- and choline-containing metabolites were measured in the basal ganglia and pons, no significant differences were found between veterans with or without GWI, suggesting that GWI is not associated with reduced NAA in these regions. Veterans with GWI had significantly higher rates of Post Traumatic Stress Disorder (PTSD), supporting the idea that GWI symptoms are stress-related.

Objectives

Memory impairment is one of the most prominent cognitive deficits in temporal lobe epilepsy (TLE). The overall goal of this study was to explore the contribution of cortical and hippocampal (subfield) damage to impairment of auditory immediate recall (AIMrecall), auditory delayed recall (ADMrecall), and auditory delayed recognition (ADMrecog) of the Wechsler Memory Scale III (WMS-III) in TLE with (TLE–MTS) and without hippocampal sclerosis (TLE-no). It was hypothesized that volume loss in different subfields determines memory impairment in TLE–MTS and temporal neocortical thinning in TLE-no.

Methods

T1 whole brain and T2-weighted hippocampal magnetic resonance imaging and WMS-III were acquired in 22 controls, 18 TLE–MTS, and 25 TLE-no. Hippocampal subfields were determined on the T2 image. Free surfer was used to obtain cortical thickness averages of temporal, frontal, and parietal cortical regions of interest (ROI). MANOVA and stepwise regression analysis were used to identify hippocampal subfields and cortical ROI significantly contributing to AIMrecall, ADMrecall, and ADMrecog.

Results

In TLE–MTS, AIMrecall was associated with cornu ammonis 3 (CA3) and dentate (CA3&DG) and pars opercularis, ADMrecall with CA1 and pars triangularis, and ADMrecog with CA1. In TLE-no, AIMrecall was associated with CA3&DG and fusiform gyrus (FUSI), and ADMrecall and ADMrecog were associated with FUSI.

Conclusion

The study provided the evidence for different structural correlates of the verbal memory impairment in TLE–MTS and TLE-no. In TLE–MTS, the memory impairment was mainly associated by subfield-specific hippocampal and inferior frontal cortical damage. In TLE-no, the impairment was associated by mesial–temporal cortical and to a lesser degree hippocampal damage.

Background

Decreased hippocampal volume is described in posttraumatic stress disorder (PTSD) and depression. However, it is not known whether it is a risk factor for the development of PTSD or a consequence of PTSD. We sought to determine the effects of PTSD and depressive symptoms on hippocampal volume.

Methods

Clinical and magnetic resonance imaging data were collected in a cross sectional study of 244 Gulf War veterans. Measures included lifetime and current Clinician Administered PTSD Scale, Hamilton Depression Scale, Life Stressor Checklist, and Lifetime Drinking History. Magnetic resonance imaging data were acquired with a 1.5-T scanner and analyzed with automated and semiautomated image processing techniques.

Results

Eighty-two veterans had lifetime PTSD, 44 had current PTSD, and 38 had current depression. In the linear regression analysis, current PTSD symptoms (standardized coefficient β = −.25, p = .03) but neither lifetime PTSD symptoms nor current depression were associated with smaller hippocampal volume. Gender, age, history of early life trauma, education, lifetime and current alcohol use, current marijuana use, and treatment with antidepressants did not have independent effects. Participants with chronic PTSD had, on average, a smaller hippocampus compared with those with remitted PTSD.

Conclusions

The finding that current but not lifetime PTSD symptom severity explains hippocampal size raises two possibilities: either a small hippocampus is a risk factor for lack of recovery from PTSD (trait) or PTSD effects on hippocampal volume are reversible once PTSD symptoms remit and the patient recovers (state).

Objectives

To assess the clinical characteristics and course of patients with mild cognitive impairment (MCI) and mild Alzheimer disease (AD) treated with cholinesterase inhibitors (ChEIs) and memantine hydrochloride.

Design

Cohort study.

Setting

The 59 recruiting sites for the Alzheimer’s Disease Neuroimaging Initiative (ADNI).

Participants

Outpatients with MCI and AD in ADNI.

Main Outcome Measures

The AD Assessment Scale–cognitive subscale (ADAS-cog), Mini-Mental State Examination (MMSE), Clinical Dementia Rating (CDR) scale, and Functional Activities Questionnaire (FAQ).

Results

A total of 177 (44.0%) of 402 MCI patients and 159 (84.6%) of 188 mild-AD patients were treated with ChEIs and 11.4% of MCI patients and 45.7% of AD patients with memantine at entry. Mild-cognitive-impairment patients who received ChEIs with or without memantine were more impaired, showed greater decline in scores, and progressed to dementia sooner than patients who did not receive ChEIs. Alzheimer-disease patients who received ChEIs and memantine took them longer, were more functionally impaired, and showed greater decline on the MMSE and CDR (but not on the ADAS-cog or FAQ) than those who received ChEIs only.

Conclusions

Academic physicians frequently prescribe ChEIs and memantine earlier than indicated in the US Food and Drug Administration–approved labeling to patients who are relatively more severely impaired or who are rapidly progressing toward cognitive impairment. The use of these medications in ADNI is associated with clinical decline and may affect the interpretation of clinical trial outcomes.

Study Registration

clinicalTrials.gov Identifier: NCT00106899

Posttraumatic stress disorder (PTSD) accounts for a substantial proportion of casualties among surviving soldiers of the Iraq and Afghanistan wars. Currently, the assessment of PTSD is based exclusively on symptoms, making it difficult to obtain an accurate diagnosis. This study aimed to find potential imaging markers for PTSD using structural, perfusion and diffusion magnetic resonance imaging (MRI) together. Seventeen male veterans with PTSD (45 ± 14 years old) and 15 age-matched male veterans without PTSD had measurements of regional cerebral blood flow (rCBF) using arterial spin labeling (ASL) perfusion MRI. A slightly larger group had also measurements of white matter integrity using diffusion tensor imaging (DTI) with computations of regional fractional anisotropy (FA). The same subjects also had structural MRI of the hippocampal subfields as reported recently (W. Zhen et al. Arch Gen Psych 2010; 67(3):296–303). On ASL-MRI, subjects with PTSD had increased rCBF in primarily right parietal and superior temporal cortices. On DTI, subjects with PTSD had FA reduction in white matter regions of the prefrontal lobe, including areas near the anterior cingulate cortex and prefrontal cortex as well as in the posterior angular gyrus. In conclusion, PTSD is associated with a systematic pattern of physiological and structural abnormalities in predominantly frontal lobe and limbic brain regions. Structural, perfusion and diffusion MRI together may provide a signature for a PTSD marker.

Genetic mapping of hippocampal shape, an under-explored area, has strong potential as a neurodegeneration biomarker for AD and MCI. This study investigates the genetic effects of top candidate single nucleotide polymorphisms (SNPs) on hippocampal shape features as quantitative traits (QTs) in a large cohort. FS+LDDMM was used to segment hippocampal surfaces from MRI scans and shape features were extracted after surface registration. Elastic net (EN) and sparse canonical correlation analysis (SCCA) were proposed to examine SNP-QT associations, and compared with multiple regression (MR). Although similar in power, EN yielded substantially fewer predictors than MR. Detailed surface mapping of global and localized genetic effects were identified by MR and EN to reveal multi-SNP-single-QT relationships, and by SCCA to discover multi-SNP-multi-QT associations. Shape analysis identified stronger SNP-QT correlations than volume analysis. Sparse multivariate models have greater power to reveal complex SNP-QT relationships. Genetic analysis of quantitative shape features has considerable potential for enhancing mechanistic understanding of complex disorders like AD.

We implemented least absolute shrinkage and selection operator (LASSO) regression to evaluate gene effects in genome-wide association studies (GWAS) of brain images, using an MRI-derived temporal lobe volume measure from 729 subjects scanned as part of the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Sparse groups of SNPs in individual genes were selected by LASSO, which identifies efficient sets of variants influencing the data. These SNPs were considered jointly when assessing their association with neuroimaging measures. We discovered 22 genes that passed genome-wide significance for influencing temporal lobe volume. This was a substantially greater number of significant genes compared to those found with standard, univariate GWAS. These top genes are all expressed in the brain and include genes previously related to brain function or neuropsychiatric disorders such as MACROD2, SORCS2, GRIN2B, MAGI2, NPAS3, CLSTN2, GABRG3, NRXN3, PRKAG2, GAS7, RBFOX1, ADARB2, CHD4, and CDH13. The top genes we identified with this method also displayed significant and widespread post hoc effects on voxelwise, tensor-based morphometry (TBM) maps of the temporal lobes. The most significantly associated gene was an autism susceptibility gene known as MACROD2. We were able to successfully replicate the effect of the MACROD2 gene in an independent cohort of 564 young, Australian healthy adult twins and siblings scanned with MRI (mean age: 23.8 ± 2.2 SD years). Our approach powerfully complements univariate techniques in detecting influences of genes on the living brain.

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.