Sarah K. Madsen

Genetics of Brain Fiber Architecture and Intellectual Performance

The study is the first to analyze genetic and environmental factors that affect brain fiber architecture and its genetic linkage with cognitive function. We assessed white matter integrity voxelwise using diffusion tensor imaging at high magnetic field (4 Tesla), in 92 identical and fraternal twins. White matter integrity, quantified using fractional anisotropy (FA), was used to fit structural equation models (SEM) at each point in the brain, generating three-dimensional maps of heritability. We visualized the anatomical profile of correlations between white matter integrity and full-scale, verbal, and performance intelligence quotients (FIQ, VIQ, and PIQ). White matter integrity (FA) was under strong genetic control and was highly heritable in bilateral frontal (a2 = 0.55, p = 0.04, left; a2 = 0.74, p = 0.006, right), bilateral parietal (a2 = 0.85, p < 0.001, left; a2 = 0.84, p < 0.001, right), and left occipital (a2 = 0.76, p = 0.003) lobes, and was correlated with FIQ and PIQ in the cingulum, optic radiations, superior fronto-occipital fasciculus, internal capsule, callosal isthmus, and the corona radiata (p = 0.04 for FIQ and p = 0.01 for PIQ, corrected for multiple comparisons). In a cross-trait mapping approach, common genetic factors mediated the correlation between IQ and white matter integrity, suggesting a common physiological mechanism for both, and common genetic determination. These genetic brain maps reveal heritable aspects of white matter integrity and should expedite the discovery of single-nucleotide polymorphisms affecting fiber connectivity and cognition.

Automated mapping of hippocampal atrophy in 1-year repeat MRI data from 490 subjects with Alzheimer’s disease, mild cognitive impairment, and elderly controls

As one of the earliest structures to degenerate in Alzheimers disease (AD), the hippocampus is the target of many studies of factors that influence rates of brain degeneration in the elderly. In one of the largest brain mapping studies to date, we mapped the 3D profile of hippocampal degeneration over time in 490 subjects scanned twice with brain MRI over a 1-year interval (980 scans). We examined baseline and 1-year follow-up scans of 97 AD subjects (49 males/48 females), 148 healthy control subjects (75 males/73 females), and 245 subjects with mild cognitive impairment (MCI; 160 males/85 females). We used our previously validated automated segmentation method, based on AdaBoost, to create 3D hippocampal surface models in all 980 scans. Hippocampal volume loss rates increased with worsening diagnosis (normal=0.66%/year; MCI=3.12%/year; AD=5.59%/year), and correlated with both baseline and interval changes in Mini-Mental State Examination (MMSE) scores and global and sum-of-boxes Clinical Dementia Rating scale (CDR) scores. Surface-based statistical maps visualized a selective profile of ongoing atrophy in all three diagnostic groups. Healthy controls carrying the ApoE4 gene atrophied faster than non-carriers, while more educated controls atrophied more slowly; converters from MCI to AD showed faster atrophy than non-converters. Hippocampal loss rates can be rapidly mapped, and they track cognitive decline closely enough to be used as surrogate markers of Alzheimers disease in drug trials. They also reveal genetically greater atrophy in cognitively intact subjects.

Validation of a Fully Automated 3D Hippocampal Segmentation Method Using Subjects with Alzheimer's Disease, Mild Cognitive Impairment, and Elderly Controls

We introduce a new method for brain MRI segmentation, called the auto context model (ACM), to segment the hippocampus automatically in 3D T1-weighted structural brain MRI scans of subjects from the Alzheimers Disease Neuroimaging Initiative (ADNI). In a training phase, our algorithm used 21 hand-labeled segmentations to learn a classification rule for hippocampal versus non-hippocampal regions using a modified AdaBoost method, based on approximately 18,000 features (image intensity, position, image curvatures, image gradients, tissue classification maps of gray/white matter and CSF, and mean, standard deviation, and Haar filters of size 1x1x1 to 7x7x7). We linearly registered all brains to a standard template to devise a basic shape prior to capture the global shape of the hippocampus, defined as the pointwise summation of all the training masks. We also included curvature, gradient, mean, standard deviation, and Haar filters of the shape prior and the tissue classified images as features. During each iteration of ACM - our extension of AdaBoost - the Bayesian posterior distribution of the labeling was fed back in as an input, along with its neighborhood features as new features for AdaBoost to use. In validation studies, we compared our results with hand-labeled segmentations by two experts. Using a leave-one-out approach and standard overlap and distance error metrics, our automated segmentations agreed well with human raters; any differences were comparable to differences between trained human raters. Our error metrics compare favorably with those previously reported for other automated hippocampal segmentations, suggesting the utility of the approach for large-scale studies.

Automated 3D Mapping of Hippocampal Atrophy and its Clinical Correlates in 400 Subjects with Alzheimer’s Disease, Mild Cognitive Impairment, and Elderly Controls

We used a new method we developed for automated hippocampal segmentation, called the auto context model, to analyze brain MRI scans of 400 subjects from the Alzheimers disease neuroimaging initiative. After training the classifier on 21 hand‐labeled expert segmentations, we created binary maps of the hippocampus for three age‐ and sex‐matched groups: 100 subjects with Alzheimers disease (AD), 200 with mild cognitive impairment (MCI) and 100 elderly controls (mean age: 75.84; SD: 6.64). Hippocampal traces were converted to parametric surface meshes and a radial atrophy mapping technique was used to compute average surface models and local statistics of atrophy. Surface‐based statistical maps visualized links between regional atrophy and diagnosis (MCI versus controls: P = 0.008; MCI versus AD: P = 0.001), mini‐mental state exam (MMSE) scores, and global and sum‐of‐boxes clinical dementia rating scores (CDR; all P < 0.0001, corrected). Right but not left hippocampal atrophy was associated with geriatric depression scores (P = 0.004, corrected); hippocampal atrophy was not associated with subsequent decline in MMSE and CDR scores, educational level, ApoE genotype, systolic or diastolic blood pressure measures, or homocysteine. We gradually reduced sample sizes and used false discovery rate curves to examine the methods power to detect associations with diagnosis and cognition in smaller samples. Forty subjects were sufficient to discriminate AD from normal and correlate atrophy with CDR scores; 104, 200, and 304 subjects, respectively, were required to correlate MMSE with atrophy, to distinguish MCI from normal, and MCI from AD. Hum Brain Mapp 2009.

Brain Differences in Infants at Differential Genetic Risk for Late-Onset Alzheimer Disease: A Cross-sectional Imaging Study

IMPORTANCE Converging evidence suggests brain structure alterations may precede overt cognitive impairment in Alzheimer disease by several decades. Early detection of these alterations holds inherent value for the development and evaluation of preventive treatment therapies. OBJECTIVE To compare magnetic resonance imaging measurements of white matter myelin water fraction (MWF) and gray matter volume (GMV) in healthy infant carriers and noncarriers of the apolipoprotein E (APOE) ε4 allele, the major susceptibility gene for late-onset AD. DESIGN, SETTING, AND PARTICIPANTS Quiet magnetic resonance imaging was performed at an academic research imaging center on 162 healthy, typically developing 2- to 25-month-old infants with no family history of Alzheimer disease or other neurological or psychiatric disorders. Cross-sectional measurements were compared in the APOE ε4 carrier and noncarrier groups. White matter MWF was compared in one hundred sixty-two 2- to 25-month-old sleeping infants (60 ε4 carriers and 102 noncarriers). Gray matter volume was compared in a subset of fifty-nine 6- to 25-month-old infants (23 ε4 carriers and 36 noncarriers), who remained asleep during the scanning session. The carrier and noncarrier groups were matched for age, gestational duration, birth weight, sex ratio, maternal age, education, and socioeconomic status. MAIN OUTCOMES AND MEASURES Automated algorithms compared regional white matter MWF and GMV in the carrier and noncarrier groups and characterized their associations with age. RESULTS Infant ε4 carriers had lower MWF and GMV measurements than noncarriers in precuneus, posterior/middle cingulate, lateral temporal, and medial occipitotemporal regions, areas preferentially affected by AD, and greater MWF and GMV measurements in extensive frontal regions and measurements were also significant in the subset of 2- to 6-month-old infants (MWF differences, P < .05, after correction for multiple comparisons; GMV differences, P < .001, uncorrected for multiple comparisons). Infant ε4 carriers also exhibited an attenuated relationship between MWF and age in posterior white matter regions. CONCLUSIONS AND RELEVANCE While our findings should be considered preliminary, this study demonstrates some of the earliest brain changes associated with the genetic predisposition to AD. It raises new questions about the role of APOE in normal human brain development, the extent to which these processes are related to subsequent AD pathology, and whether they could be targeted by AD prevention therapies.

Subcortical brain atrophy persists even in HAART-regulated HIV disease

The purpose of this study was to determine the pattern and extent of caudate nucleus and putamen atrophy in HIV-infected men with well-controlled immune status and viral replication. 155 men underwent structural brain magnetic resonance imaging; 84 were HIV-infected and 71 were uninfected controls. MRI data were processed using the Fully Deformable Segmentation routine, producing volumes for the right and left caudate nucleus and putamen, and 3-D maps of spatial patterns of thickness. There was significant atrophy in the HIV-infected men in both the caudate and putamen, principally in the anterior regions. The volume of the basal ganglia was inversely associated with the time since first seropositivity, suggesting that either there is a chronic, subclinical process that continues in spite of therapy, or that the extent of the initial insult caused the extent of atrophy.

Mapping correlations between ventricular expansion and CSF amyloid and tau biomarkers in 240 subjects with Alzheimer’s disease, mild cognitive impairment and elderly controls

We aimed to improve on the single-atlas ventricular segmentation method of (Carmichael, O.T., Thompson, P.M., Dutton, R.A., Lu, A., Lee, S.E., Lee, J.Y., Kuller, L.H., Lopez, O.L., Aizenstein, H.J., Meltzer, C.C., Liu, Y., Toga, A.W., Becker, J.T., 2006. Mapping ventricular changes related to dementia and mild cognitive impairment in a large community-based cohort. IEEE ISBI. 315-318) by using multi-atlas segmentation, which has been shown to lead to more accurate segmentations (Chou, Y., Leporé, N., de Zubicaray, G., Carmichael, O., Becker, J., Toga, A., Thompson, P., 2008. Automated ventricular mapping with multi-atlas fluid image alignment reveals genetic effects in Alzheimers disease, NeuroImage 40(2): 615-630); with this method, we calculated minimal numbers of subjects needed to detect correlations between clinical scores and ventricular maps. We also assessed correlations between emerging CSF biomarkers of Alzheimers disease pathology and localizable deficits in the brain, in 80 AD, 80 mild cognitive impairment (MCI), and 80 healthy controls from the Alzheimers Disease Neuroimaging Initiative. Six expertly segmented images and their embedded parametric mesh surfaces were fluidly registered to each brain; segmentations were averaged within subjects to reduce errors. Surface-based statistical maps revealed powerful correlations between surface morphology and 4 variables: (1) diagnosis, (2) depression severity, (3) cognitive function at baseline, and (4) future cognitive decline over the following year. Cognitive function was assessed using the mini-mental state exam (MMSE), global and sum-of-boxes clinical dementia rating (CDR) scores, at baseline and 1-year follow-up. Lower CSF Abeta(1-42) protein levels, a biomarker of AD pathology assessed in 138 of the 240 subjects, were correlated with lateral ventricular expansion. Using false discovery rate (FDR) methods, 40 and 120 subjects, respectively, were needed to discriminate AD and MCI from normal groups. 120 subjects were required to detect correlations between ventricular enlargement and MMSE, global CDR, sum-of-boxes CDR and clinical depression scores. Ventricular expansion maps correlate with pathological and cognitive measures in AD, and may be useful in future imaging-based clinical trials.

3D maps localize caudate nucleus atrophy in 400 Alzheimer’s disease, mild cognitive impairment, and healthy elderly subjects

MRI research examining structural brain atrophy in Alzheimers disease (AD) generally focuses on medial temporal and cortical structures, but amyloid and tau deposits also accumulate in the caudate. Here we mapped the 3D profile of caudate atrophy using a surface mapping approach in subjects with AD and mild cognitive impairment (MCI) to identify potential clinical and pathological correlates. 3D surface models of the caudate were automatically extracted from 400 baseline MRI scans (100 AD, 200 MCI, 100 healthy elderly). Compared to controls, caudate volumes were lower in MCI (2.64% left, 4.43% right) and AD (4.74% left, 8.47% right). Caudate atrophy was associated with age, sum-of-boxes and global Clinical Dementia Ratings, Delayed Logical Memory scores, MMSE decline 1 year later, and body mass index. Reduced right (but not left) volume was associated with MCI-to-AD conversion and CSF tau levels. Normal caudate asymmetry (with the right 3.9% larger than left) was lost in AD, suggesting preferential right caudate atrophy. Automated caudate maps may complement other MRI-derived measures of disease burden in AD.

Brain Structure Changes Visualized in Early- and Late-Onset Blind Subjects

We examined 3D patterns of volume differences in the brain associated with blindness, in subjects grouped according to early and late onset. Using tensor-based morphometry, we mapped volume reductions and gains in 16 early-onset (EB) and 16 late-onset (LB) blind adults (onset <5 and >14 years old, respectively) relative to 16 matched sighted controls. Each subjects structural MRI was fluidly registered to a common template. Anatomical differences between groups were mapped based on statistical analysis of the resulting deformation fields revealing profound deficits in primary and secondary visual cortices for both blind groups. Regions outside the occipital lobe showed significant hypertrophy, suggesting widespread compensatory adaptations. EBs but not LBs showed deficits in the splenium and the isthmus. Gains in the non-occipital white matter were more widespread in the EBs. These differences may reflect regional alterations in late neurodevelopmental processes, such as myelination, that continue into adulthood.

Sex differences in brain structure in auditory and cingulate regions

We applied a new method to visualize the three-dimensional profile of sex differences in brain structure based on MRI scans of 100 young adults. We compared 50 men with 50 women, matched for age and other relevant demographics. As predicted, left hemisphere auditory and language-related regions were proportionally expanded in women versus men, suggesting a possible structural basis for the widely replicated sex differences in language processing. In men, primary visual, and visuo-spatial association areas of the parietal lobes were proportionally expanded, in line with prior reports of relative strengths in visuo-spatial processing in men. We relate these three-dimensional patterns to prior functional and structural studies, and to theoretical predictions based on nonlinear scaling of brain morphometry.