Ellen Dicks

Gray matter network measures are associated with cognitive decline in mild cognitive impairment

Gray matter networks are disrupted in Alzheimers disease and related to cognitive impairment. However, it is still unclear whether these disruptions are associated with cognitive decline over time. Here, we studied this question in a large sample of patients with mild cognitive impairment with extensive longitudinal neuropsychological assessments. Gray matter networks were extracted from baseline structural magnetic resonance imaging, and we tested associations of network measures and cognitive decline in Mini-Mental State Examination and 5 cognitive domains (i.e., memory, attention, executive function, visuospatial, and language). Disrupted network properties were cross-sectionally related to worse cognitive impairment. Longitudinally, lower small-world coefficient values were associated with a steeper decline in almost all domains. Lower betweenness centrality values correlated with a faster decline in Mini-Mental State Examination and memory, and at a regional level, these associations were specific for the precuneus, medial frontal, and temporal cortex. Furthermore, network measures showed additive value over established biomarkers in predicting cognitive decline. Our results suggest that gray matter network measures might have use in identifying patients who will show fast disease progression.

A more randomly organized grey matter network is associated with deteriorating language and global cognition in individuals with subjective cognitive decline

Grey matter network disruptions in Alzheimers disease (AD) are associated with worse cognitive impairment cross‐sectionally. Our aim was to investigate whether indications of a more random network organization are associated with longitudinal decline in specific cognitive functions in individuals with subjective cognitive decline (SCD).

Atrophy subtypes in prodromal Alzheimer’s disease are associated with cognitive decline

Alzheimers disease is a heterogeneous disorder. Understanding the biological basis for this heterogeneity is key for developing personalized medicine. We identified atrophy subtypes in Alzheimers disease dementia and tested whether these subtypes are already present in prodromal Alzheimers disease and could explain interindividual differences in cognitive decline. First we retrospectively identified atrophy subtypes from structural MRI with a data-driven cluster analysis in three datasets of patients with Alzheimers disease dementia: discovery data (dataset 1: n = 299, age = 67 ± 8, 50% female), and two independent external validation datasets (dataset 2: n = 181, age = 66 ± 7, 52% female; dataset 3: n = 227, age = 74 ± 8, 44% female). Subtypes were compared on clinical, cognitive and biological characteristics. Next, we classified prodromal Alzheimers disease participants (n = 603, age = 72 ± 8, 43% female) according to the best matching subtype to their atrophy pattern, and we tested whether subtypes showed cognitive decline in specific domains. In all Alzheimers disease dementia datasets we consistently identified four atrophy subtypes: (i) medial-temporal predominant atrophy with worst memory and language function, older age, lowest CSF tau levels and highest amount of vascular lesions; (ii) parieto-occipital atrophy with poor executive/attention and visuospatial functioning and high CSF tau; (iii) mild atrophy with best cognitive performance, young age, but highest CSF tau levels; and (iv) diffuse cortical atrophy with intermediate clinical, cognitive and biological features. Prodromal Alzheimers disease participants classified into one of these subtypes showed similar subtype characteristics at baseline as Alzheimers disease dementia subtypes. Compared across subtypes in prodromal Alzheimers disease, the medial-temporal subtype showed fastest decline in memory and language over time; the parieto-occipital subtype declined fastest on executive/attention domain; the diffuse subtype in visuospatial functioning; and the mild subtype showed intermediate decline in all domains. Robust atrophy subtypes exist in Alzheimers disease with distinct clinical and biological disease expression. Here we observe that these subtypes can already be detected in prodromal Alzheimers disease, and that these may inform on expected trajectories of cognitive decline.

DECLINE IN GREY MATTER CONNECTIVITY OVER TIME IS RELATED TO CLINICAL PROGRESSION IN MCI DUE TO AD

subtyping algorithms, including more impaired executive function in the Cortical subtype. Concordance using the two norming approaches was good overall, but the choice of norming approach did affect the distribution of N+ subtypes, especially in more advanced disease stages. The method is easily implementable, enables vMRI-based stratification in AD trials, and may help as a covariate in models explaining different cognitive presentations.

CORTICAL T1-W/T2-W RATIO VALUES ARE HIGHER IN ALZHEIMER’S DISEASE COMPARED TO CONTROLS

data, DM was not associated with PiB binding but was associated with FDG uptake (Figure) in a bilateral posterior cingulate cluster (voxels 1⁄4 948, Tmax 1⁄4 4.42, Pvoxel <.001, x, y, z 1⁄4 6, -22, 28). Conclusions: A disease marker for AD derived from routine T1 MRI scans outperforms CSF measures for tracking risk for disease progression in midlife. Such measures have great promise for facilitating broad-based early detection of AD.

IMPAIRMENT IN COMPLEX ACTIVITIES OF DAILY LIVING IS RELATED TO NEURODEGENERATION IN ALZHEIMER’S DISEASE SPECIFIC REGIONS

Today’s emotion happy/smiling 1 33,3% 2 66,7% 1.000 good 10 50,0% 10 50,0% neutral/calm 1 100,0% 0 0,0% Face expressionbefore neutral/calm 5 38,5% 8 61,5% 0.413 happy/smiling 7 63,6% 4 36,4% Face expressionduring neutral/calm 8 100,0% 0 0,0% 0.001 excited/tense 4 25,0% 12 75,0% Verbal expressionafter sad 2 100,0% 0 0,0% <0.001 angry 2 100,0% 0 0,0% neutral/calm 5 100,0% 0 0,0% excited/tense 3 20,0% 12 80,0% Face expressionafter neutral/calm 9 100,0% 0 0,0% <0.001 excited/tense 0 0,0% 12 100,0% angry 2 100,0% 0 0,0% sad 1 100,0% 0 0,0% Poster Presentations: Tuesday, July 24, 2018 P1183

THE USE OF RESIDUAL METHODS TO CAPTURE COGNITIVE RESERVE AND STUDY CLINICAL PROGRESSION IN ALZHEIMER’S DISEASE

Figure 1. Schematic representation of an individual with high cognitive reserve (A) and an individual with low cognitive reserve (B). Compared to individual B, individual A has a higher premorbid level of cognitive functioning, and is able to maintain this premorbid level at more advanced levels of neuropathology. After their inflection point, however, individual A declines more rapidly than individual B. When both subjects first present with significant cognitive impairment (score at incident AD visit) individual Awill have more underlying pathology than individual B. Reprinted with permission from Stern, Lancet Neurol, 2012,11,1006 1012, Elsevier.

LOSS OF GREY MATTER CONNECTIVITY IN THE PRECUNEUS IS ASSOCIATED WITH FASTER ATROPHY RATES IN PRECLINICAL ALZHEIMER’S DISEASE

Figure 1. Ove efficient value scale represen with a Bonfer hemisphere. IN THE PRECUNEUS IS ASSOCIATED WITH FASTER ATROPHY RATES IN PRECLINICAL ALZHEIMER’S DISEASE Betty M. Tijms, Ellen Dicks, Philip Scheltens, Frederik Barkhof, Wiesje M. Van der Flier, Alzheimer Center and Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, Netherlands; VU University Medical Center, Amsterdam Neuroscience, Amsterdam, Netherlands; VU University Medical Center, Amsterdam, Netherlands; Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, Netherlands. Contact e-mail: b.tijms@vumc.nl

LONGITUDINAL CHANGES IN GREY MATTER CONNECTIVITY ARE RELATED TO COGNITIVE DECLINE IN PRODROMAL ALZHEIMER’S DISEASE

China; University of Oxford, Oxford, United Kingdom; Newcastle University, Newcastle upon Tyne, United Kingdom; United States Naval Academy, Annapolis, MD, USA; Rotman Research Institute, Baycrest, Toronto, ON, Canada; Brain Center Rudolf Magnus / University Medical Center Utrecht, Utrecht, Netherlands; Chosun University, Gwangju, South Korea; Massachusetts General Hospital, Boston, MA, USA; Johns Hopkins University School of Medicine, Baltimore, MD, USA; University of Cambridge, Cambridge, United Kingdom; Newcastle University, Institute of Neuroscience, Newcastle upon Tyne, United Kingdom; Southeast University, Nanjing, China; Dementia Research Centre and Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, United Kingdom; Alzheimer Center and Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, Netherlands. Contact e-mail: e.dicks@vumc.nl

GREY MATTER CONNECTIVITY IS RELATED TO A STEEPER LOSS OF MEMORY AND LANGUAGE FUNCTIONING OVER TIME IN PATIENTS WITH SUBJECTIVE COGNITIVE DECLINE

structural brain measures than with AV1451 uptake. Perhaps atrophy provides a tighter link with cognitive decline than tau pathology, possibly because NFTs precede the neurodegeneration which produces cognitive impairment and/or because tau pathology does not capture other contributors to loss of neuronal integrity. The more complementary relationship of AV1451 uptake and structural MRI 5may reflect that in early AD tangle pathology is the primary driver of neuronal integrity in this region, as opposed to language and executive networks.