A NOVEL NEUROIMAGING APPROACH TO CAPTURE COGNITIVE RESERVE

A NOVEL NEUROIMAGING APPROACH TO CAPTURE COGNITIVE RESERVE

P74 IC-P-097 Poster Presentations: Saturday, July 23, 2016 A NOVEL NEUROIMAGING APPROACH TO CAPTURE COGNITIVE RESERVE Anita C. van Loenhoud1, Alle M...

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P74 IC-P-097

Poster Presentations: Saturday, July 23, 2016 A NOVEL NEUROIMAGING APPROACH TO CAPTURE COGNITIVE RESERVE

Anita C. van Loenhoud1, Alle Meije Wink1, Colin Groot2, Sander C. J. Verfaillie1, Frederik Barkhof3, Bart N. M. van Berckel1, Philip Scheltens1, Wiesje M. van der Flier1, Rik Ossenkoppele1, 1VU University Medical Center, Amsterdam, Netherlands; 2Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, Netherlands; 3Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, Netherlands. Contact e-mail: a. [email protected] Background: Alzheimer’s disease (AD) is associated with brain

atrophy, progressive cognitive impairment and ultimately dementia. The onset and level of cognitive impairment relative to extent of atrophy, however, differs substantially between patients. The concept of cognitive reserve (CR) may explain this inter-individual heterogeneity. CR describes the ability to maintain cognitive function in the presence of neuropathology. Since it cannot be measured directly, we developed an integrative method including measures of atrophy and cognition, to capture this construct and investigate associations with a CR proxy (i.e. education). Methods: We included 511 amyloid-positive patients in different stages along the AD Table 1 Demographic and clinical characteristics for the total sample and each diagnostic group

N diagnosis (n) age sex (% male) education (scale: 1-7)a MMSE TIV W-score (whole-brain)

total

non-demented

demented

511 66.5 (7.3) 51.7 5.0 (1-7) 22.8 (4.6) 1.5 (.17) .0 (.47)

164 SCD (56) MCI (108) 66.6 (7.3) 57.3 6.0 (1-7) 27.0 (2.2) 1.5 (.16) .13 (.47)

347 AD (347) 66.4 (7.3) 49.0 5.0 (1-7) 20.9 (4.2) 1.5 (.17) -.06 (.46)

Data are presented as mean (SD) unless indicated otherwise. MMSE ¼ Mini-Mental State Examination, TIV ¼ total intracranial volume in dm3, SCD ¼ subjective cognitive decline, MCI ¼ mild cognitive impairment, AD ¼ Alzheimer’s disease dementia. a Data represent median (range).

Figure 1. Mean W-score in the whole-brain (green bars) and temporoparietal (blue bars) mask for the total sample, across three levels of education (i.e. low [1 to 3]; intermediate [4 and 5]; high [6 and 7]).

Figure 2. W-scores in each gray matter voxel in the total sample for patients with low (left), intermediate (middle) and high (right) educational levels. Low CR is reflected by positive W- scores, high CR by negative W-scores.

Figure 3. Brain regions showing a negative relationship (in neurological convention) between W-scores and education (p<.05, corrected for multiple comparisons using threshold-free cluster enhancement), adjusted for clinical severity (i.e. demented vs. non-demented). This indicates that, across different stages of the AD spectrum, highly educated patients could tolerate more atrophy (i.e. lower GM volumes) while maintaining cognitive function than patients with lower education. W-scores were generated based on a voxel-wise regression with MMSE as a predictor for gray matter volume, adjusted for age, sex, total intracranial volume and scanner type.

spectrum (see Table 1) with available 3T magnetic resonance imaging. We regressed gray matter (GM) volume in each voxel on global cognition (i.e. Mini-Mental State Examination [MMSE] score), adjusted for age, sex, total intracranial volume and scanner type. Standardized residuals at the voxel level (i.e. W-scores) were used as a measure of CR (see Figures 1 and 2). Negative W-scores indicated more atrophy than expected based on MMSE score (i.e. high CR), while positive W-scores reflected less atrophy than expected (i.e. low CR). To validate our method, we performed Spearman’s rank order correlations between education (measured on a standardized 7-point scale) and mean W-scores in either a whole-brain or AD signature temporoparietal (TP) mask, as well as a nonparametric whole-brain voxel-wise analysis of the effect of education on W-scores. These latter analyses were adjusted for clinical severity (i.e. demented, n¼347, vs. non-demented, n¼164). Results: We observed significant correlations between education and mean W-scores (indicating that higher education related to more CR) in the TP (r¼-.163, p<.001) and whole-brain mask (r¼-.120, p<.01). In the voxel-wise analysis, this effect was most prominent in the right superior lateral occipital, bilateral inferior parietal and inferior and middle temporal cortex (p<.05, corrected for multiple comparisons [see Figure 3]). Conclusions: This novel neuroimaging approach captures CR in high anatomical detail at the individual level. Our methods yields a standardized measure and can be modified (using different neuroimaging and cognitive parameters) and broadly applied (to

Poster Presentations: Saturday, July 23, 2016

various types of pathology and CR proxies), making it a promising tool for future studies. IC-P-098

FUNCTIONAL CONNECTIVITY WITH ANTERIOR TEMPORAL LOBE REGIONS ORDERED ACCORDING TO THE BRAAK PROGRESSION SCHEME REVEALS SEQUENTIAL COUPLING TO DEFAULT MODE AND THEN SENSORY NETWORKS

Adam J. Schwarz1, Brian A. Gordon2, Aaron Tanenbaum3, John C. Morris3,4, Tammie LS. Benzinger4,5, Beau Ances4,6, 1Eli Lilly and Company, Indianapolis, IN, USA; 2Washington University School of Medicine, St. Louis, MO, USA; 3Washington University in St. Louis, St. Louis, MO, USA; 4Knight Alzheimer’s Disease Research Center, St. Louis, MO, USA; 5Washington University in St. Louis School of Medicine, St. Louis, MO, USA; 6Washington University School of Medicine, St. Louis, MO, USA. Contact e-mail: [email protected] Background: The stereotypical picture of tau spreading in the Alz-

heimer’s brain is encapsulated in the Braak staging scheme, which posits a medial to lateral progression of tau pathology around the anterior temporal lobe that parallels a subsequent spreading of tau to the wider neocortex. Association cortices are affected before primary sensory areas. This spreading is thought to occur via distributed functional networks. We sought to understand the whole-brain functional connectivity relationships with respect to Braak staging regions in the anterior temporal lobe, to elucidate the a possible sequence of involvement of wider neocortical brain networks associated with the prototypical scheme of tau progression. Methods: Regions of interest were defined corresponding to the anterior temporal lobe regions specified in the simplified Braak staging procedure [1,2]. To profile the connectivity of these regions in the absence of overt Alzheimer’s pathology, we examined a cohort of older cognitively normal subjects (CDR¼0, N¼ 126, Age 45-88) and a cohort of young healthy male volunteers (N¼16). Whole-brain, seed-based connectivity profiles, and contrasts in connectivity between different Braak regions, were computed. Results: In both groups, as the seed was moved from medial (entorhinal cortex) to lateral (superior temporal gyrus (STG)), connectivity with the default mode network (DMN) first increased (reaching a maximum at the middle temporal gyrus (MTG)) but then sharply decreased at the STG. In contrast, con-

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nectivity with the sensorimotor network (SMN) increased sharply with respect to the STG relative to the MTG (Figure). Contrast maps between connectivity patterns illustrate this selective increased and decreased connectivity with the DMN (Figure). Patterns in both groups were similar, except the younger subjects showed strong DMN correlations with the inferior temporal gyrus as well as the MTG. Conclusions: Considering the anterior temporal Braak regions as representing a temporal ordering from medial to lateral, the observed dependence of functional connectivity is consistent with regions such as the precuneus exhibiting tau pathology before primary sensory areas. Future work will consider how this connectivity is modified by the presence of tau pathology. [1] Braak H et al. 2006 Acta Neuropathol 112(4): 389-404. [2] Schwarz AJ et al. 2016 Brain (in press). IC-P-099

SYNERGISM BETWEEN BRAIN AMYLOID ACCUMULATION AND NEURONAL INJURY IN CORTICAL-SUBCORTICAL CIRCUITS CAUSES MEMORY DECLINES IN ANIMAL MODELS

Min Su Kang1,2,3,4, Eduardo R. Zimmer5,6, Maxime J. Parent7, Sulantha S. Mathotaarachchi2,3,4, Tharick A. Pascoal2,3,4,8,9, Monica Shin2,4, Antonio Aliaga3, Andrea Lessa Benedet10, Sonia Do Carmo11, Jean-Paul Soucy3,12,13,14, Serge Gauthier2,8, A. Claudio Cuello3, Pedro Rosa-Neto2,4,8,12,15, 1Douglas Mental Health Institute, Montreal, QC, Canada; 2McGill University Research Centre for Studies in Aging, Verdun, QC, Canada; 3McGill University, Montreal, QC, Canada; 4Translational Neuroimaging Laboratory- McGill University, Verdun, QC, Canada; 5Federal University of Rio Grande dos Sul, Porto Alegre, Brazil; 6Brain Institute of Rio Grande do Sul, Porto Alegre, Brazil; 7 Yale School of Medicine, New Haven, CT, USA; 8Douglas Hospital Research Centre, Verdun, QC, Canada; 9Centre for Studies on Prevention of Alzheimer’s Disease (StoP-AD Centre), Douglas Mental Health Institute, Verdun, QC, Canada; 10Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Montreal, QC, Canada; 11 Department of Pharmacology-McGill University, Montreal, QC, Canada; 12 McConnell Brain Imaging Centre, Montreal, QC, Canada; 13Montreal Neurological Institute, Montreal, QC, Canada; 14Universite de Montreal, Montreal, QC, Canada; 15Centre for Studies on Prevention of Alzheimer’s Disease (StoP-AD Centre), Douglas Mental Health Institute, Verdun, QC, Canada. Contact e-mail: [email protected] Background: A decline in cerebrospinal fluid (CSF) Ab1-42 is a pathological biomarker and has been reported to be inversely associated with Ab plaque load in the brain. Also, the cerebral metabolic rate of glucose, as measured by [18F]Fluorodeoxyglucose ([18F]FDG) in Positron Emission Tomography (PET), is widely used as a biomarker of neurodegeneration, which has been shown to be closely related to the cognitive decline observed in Alzheimer’s Disease (AD). Here, we aim to show the synergistic effect of the regional cerebral hypometabolism with increase Ab load, as represented as a decline in CSF Ab1-42, on cognitive decline in McGill-R-Thy1-APP transgenic rat model. This transgenic rat models full AD like amyloid pathology, providing a platform to explore the impact of amyloid pathology on imaging biomarkers without the bias of tau pathology invariably present in the human brain. We hypothesized that regression of CSF Ab1-42 level with the regional cerebral hypometabolism would have a synergistic effect on cognitive decline. Methods: A total of 9 Tg were used for this study. The FDG-PET acquisition, Morris Water Maze (MWM), and CSF collection were done longitudinally with 11.5 mo (baseline) and 16.8 mo (follow-up). Individual FDG SUVRs were generated using pons as a reference region. The synergistic effect of hypometabolism and Ab is demonstrated using