Sara Mohades

Dissociation between Brain Amyloid Deposition and Metabolism in Early Mild Cognitive Impairment

Background The hypothetical model of dynamic biomarkers for Alzheimer’s disease (AD) describes high amyloid deposition and hypometabolism at the mild cognitive impairment (MCI) stage. However, it remains unknown whether brain amyloidosis and hypometabolism follow the same trajectories in MCI individuals. We used the concept of early MCI (EMCI) and late MCI (LMCI) as defined by the Alzheimer’s disease Neuroimaging Initiative (ADNI)-Go in order to compare the biomarker profile between EMCI and LMCI. Objectives To examine the global and voxel-based neocortical amyloid burden and metabolism among individuals who are cognitively normal (CN), as well as those with EMCI, LMCI and mild AD. Methods In the present study, 354 participants, including CN (n = 109), EMCI (n = 157), LMCI (n = 39) and AD (n = 49), were enrolled between September 2009 and November 2011 through ADNI-GO and ADNI-2. Brain amyloid load and metabolism were estimated using [18F]AV45 and [18F]fluorodeoxyglucose ([18F]FDG) PET, respectively. Uptake ratio images of [18F]AV45 and [18F]FDG were calculated by dividing the summed PET image by the median counts of the grey matter of the cerebellum and pons, respectively. Group differences of global [18F]AV45 and [18F]FDG were analyzed using ANOVA, while the voxel-based group differences were estimated using statistic parametric mapping (SPM). Results EMCI patients showed higher global [18F]AV45 retention compared to CN and lower uptake compared to LMCI. SPM detected higher [18F]AV45 uptake in EMCI compared to CN in the precuneus, posterior cingulate, medial and dorsal lateral prefrontal cortices, bilaterally. EMCI showed lower [18F]AV45 retention than LMCI in the superior temporal, inferior parietal, as well as dorsal lateral prefrontal cortices, bilaterally. Regarding to the global [18F]FDG, EMCI patients showed no significant difference from CN and a higher uptake ratio compared to LMCI. At the voxel level, EMCI showed higher metabolism in precuneus, hippocampus, entorhinal and inferior parietal cortices, as compared to LMCI. Conclusions The present results indicate that brain metabolism remains normal despite the presence of significant amyloid accumulation in EMCI. These results suggest a role for anti-amyloid interventions in EMCI aiming to delay or halt the deposition of amyloid and related metabolism impairment.

Amyloid-β and hyperphosphorylated tau synergy drives metabolic decline in preclinical Alzheimer’s disease

This study was designed to test the interaction between amyloid-β and tau proteins as a determinant of metabolic decline in preclinical Alzheimer’s disease (AD). We assessed 120 cognitively normal individuals with [18F]florbetapir positron emission tomography (PET) and cerebrospinal fluid (CSF) measurements at baseline, as well as [18F]fluorodeoxyglucose ([18F]FDG) PET at baseline and at 24 months. A voxel-based interaction model was built to test the associations between continuous measurements of CSF biomarkers, [18F]florbetapir and [18F]FDG standardized uptake value ratios (SUVR). We found that the synergistic interaction between [18F]florbetapir SUVR and CSF phosphorylated tau (p-tau) measurements, rather than the sum of their independent effects, was associated with a 24-month metabolic decline in basal and mesial temporal, orbitofrontal, and anterior and posterior cingulate cortices (P<0.001). In contrast, interactions using CSF amyloid-β1–42 and total tau biomarkers did not associate with metabolic decline over a time frame of 24 months. The interaction found in this study further support the framework that amyloid-β and hyperphosphorylated tau aggregates synergistically interact to cause downstream AD neurodegeneration. In fact, the regions displaying the metabolic decline reported here were confined to brain networks affected early by amyloid-β plaques and neurofibrillary tangles. Preventive clinical trials may benefit from using a combination of amyloid-β PET and p-tau biomarkers to enrich study populations of cognitively normal subjects with a high probability of disease progression in studies, using [18F]FDG as a biomarker of efficacy.

White Matter Abnormalities and Structural Hippocampal Disconnections in Amnestic Mild Cognitive Impairment and Alzheimer’s Disease

The purpose of this project was to evaluate white matter degeneration and its impact on hippocampal structural connectivity in patients with amnestic mild cognitive impairment, non-amnestic mild cognitive impairment and Alzheimer’s disease. We estimated white matter fractional anisotropy, mean diffusivity and hippocampal structural connectivity in two independent cohorts. The ADNI cohort included 108 subjects [25 cognitively normal, 21 amnestic mild cognitive impairment, 47 non-amnestic mild cognitive impairment and 15 Alzheimer’s disease]. A second cohort included 34 subjects [15 cognitively normal and 19 amnestic mild cognitive impairment] recruited in Montreal. All subjects underwent clinical and neuropsychological assessment in addition to diffusion and T1 MRI. Individual fractional anisotropy and mean diffusivity maps were generated using FSL-DTIfit. In addition, hippocampal structural connectivity maps expressing the probability of connectivity between the hippocampus and cortex were generated using a pipeline based on FSL-probtrackX. Voxel-based group comparison statistics of fractional anisotropy, mean diffusivity and hippocampal structural connectivity were estimated using Tract-Based Spatial Statistics. The proportion of abnormal to total white matter volume was estimated using the total volume of the white matter skeleton. We found that in both cohorts, amnestic mild cognitive impairment patients had 27-29% white matter volume showing higher mean diffusivity but no significant fractional anisotropy abnormalities. No fractional anisotropy or mean diffusivity differences were observed between non-amnestic mild cognitive impairment patients and cognitively normal subjects. Alzheimer’s disease patients had 66.3% of normalized white matter volume with increased mean diffusivity and 54.3% of the white matter had reduced fractional anisotropy. Reduced structural connectivity was found in the hippocampal connections to temporal, inferior parietal, posterior cingulate and frontal regions only in the Alzheimer’s group. The severity of white matter degeneration appears to be higher in advanced clinical stages, supporting the construct that these abnormalities are part of the pathophysiological processes of Alzheimer’s disease.

Synergistic interaction between amyloid and tau predicts the progression to dementia

Recent literature proposes that amyloid β (Aβ) and phosphorylated tau (p‐tau) synergism accelerates biomarker abnormalities in controls. Yet, it remains to be answered whether this synergism is the driving force behind Alzheimer disease (AD) dementia.

Resting state executive control network adaptations in amnestic mild cognitive impairment.

Executive dysfunction is frequently associated with episodic memory decline in amnestic mild cognitive impairment (aMCI) patients. Resting state executive control network (RS-ECN) represents a novel approach to interrogate the integrity of brain areas underlying executive dysfunction. The present study aims to investigate RS-ECN in aMCI and examine a possible link between changes in brain functional connectivity and declines in executive function. aMCI individuals (n = 13) and healthy subjects (n = 16) underwent cognitive assessment including executive function and high field functional magnetic resonance imaging. Individual RS-ECN maps were estimated using a seed-based cross-correlation method. Between groups RS-ECN functional connectivity comparison was assessed using voxel-wise statistic parametric mapping. aMCI individuals had reduced RS-ECN connectivity in the anterior cingulate cortex (ACC) and dorsal lateral prefrontal cortex (DLPFC), bilaterally. In contrast, aMCI showed increased connectivity in ventral lateral and anterior prefrontal cortex, bilaterally. Connectivity strength was associated with executive function in the ACC (r = 0.6213, p = 0.023) and right DLPFC (r = 0.6454, p = 0.017). Coexistence between connectivity declines and recruitment of brain regions outside the RS-ECN as reported here fits a brain reserve conceptual framework in which brain networks undergo remodeling in aMCI individuals.

Epistasis analysis links immune cascades and cerebral amyloidosis.

BackgroundSeveral lines of evidence suggest the involvement of neuroinflammatory changes in Alzheimer’s disease (AD) pathophysiology such as amyloidosis and neurodegeneration. In fact, genome-wide association studies (GWAS) have shown a link between genes involved in neuroinflammation and AD. In order to further investigate whether interactions between candidate genetic variances coding for neuroinflammatory molecules are associated with brain amyloid β (Aβ) fibrillary accumulation, we conducted an epistasis analysis on a pool of genes associated with molecular mediators of inflammation.Methods[18F]Florbetapir positron emission tomography (PET) imaging was employed to assess brain Aβ levels in 417 participants from ADNI-GO/2 and posteriorly 174 from ADNI-1. IL-1β, IL4, IL6, IL6r, IL10, IL12, IL18, C5, and C9 genes were chosen based on previous studies conducted in AD patients. Using the [18F]florbetapir standardized uptake value ratio (SUVR) as a quantitative measure of fibrillary Aβ, epistasis analyses were performed between two sets of markers of immune-related genes using gender, diagnosis, and apolipoprotein E (APOE) as covariates. Voxel-based analyses were also conducted. The results were corrected for multiple comparison tests. Cerebrospinal fluid (CSF) Aβ1-42/phosphorylated tau (p-tau) ratio concentrations were used to confirm such associations.ResultsEpistasis analysis unveiled two significant single nucleotide polymorphism (SNP)-SNP interactions (false discovery rate (FDR) threshold 0.1), both interactions between C9 gene (rs261752) and IL6r gene (rs4240872, rs7514452). In a combined sample, the interactions were confirmed (p ≤ 10–5) and associated with amyloid accumulation within cognitively normal and AD spectrum groups. Voxel-based analysis corroborated initial findings. CSF biomarker (Aβ1-42/p-tau) confirmed the genetic interaction. Additionally, rs4240872 and rs7514452 SNPs were shown to be associated with CSF and plasma concentrations of IL6r protein.ConclusionsCertain allele combinations involving IL6r and C9 genes are associated with Aβ burden in the brain. Hypothesis-driven search for epistasis is a valuable strategy for investigating imaging endophenotypes in complex neurodegenerative diseases.

Should a global or a regional measure of amyloidosis be used in a longitudinal study

Figure 1. Vertex-based multivariate linear regression model showing the effect of amyloid load on the rate of hypo-metabolism in each disease stage, corrected for baseline glucose metabolism, age, gender and apoe genotype. Only LMCI and AD stages show positive effect from amyloid load on hypometabolism in temporo-parietal and precuneus regions. Sulantha S. Mathotaarachchi, Sara Mohades, Monica Shin, Thomas Beaudry, Andrea Lessa Benedet, Tharick Ali Pascoal, Seqian Wang, Sarinporn Manitsirikul, Maxime J. Parent, Min Su Kang, Vladimir Fonov, Chang Oh Chung, Sr., Serge Gauthier, Pedro RosaNeto, McGill University, Montreal, QC, Canada; McGill Centre for Studies in Aging, Montreal, QC, Canada; McGill Centre for Studies in Aging/Translational Neuroimaging Laboratory, Montreal, QC, Canada; McGill Centre for Studies in Aging, Verdun, QC, Canada; McGill University Centre for Studies in Aging, Verdun, QC, Canada; Image Processing Laboratory, Montreal Neurological Institute, McGill University, Montreal, QC, Canada; Centre for Studies on Prevention of Alzheimer’s Disease (StoP-AD Centre), Douglas Mental Health Institute, Montreal, QC, Canada; Douglas Hospital Research Centre, Montreal, QC, Canada; Translational Imaging Laboratory, Montreal, QC, Canada. Contact e-mail: sulantha.s@gmail.com

GLUCOSE METABOLISM IMPACT ON FUNCTIONAL CONNECTIVITY IN ALZHEIMER'S DISEASE

Canada; McGill Center for Studies in Aging/Translational Neuroimaging Laboratory, Montreal, Quebec, Canada; McGill Center for Studies in Aging, Montreal, Quebec, Canada; McGill University, Verdun, Quebec, Canada; McGill Center for Studies in Aging/Translational Neuroimaging Laboratory, Montreal, Quebec, Canada; McGill University, Montreal, Quebec, Canada; McGill Center for Studies in Aging, Montreal, Quebec, Canada. Contact e-mail: ju_sarinporn@yahoo.com

NEURODEGENERATION AND CORTICAL ATROPHY IN [18F]FLORBETAPIR ACCUMULATORS AND NON-ACCUMULATORS

BBSI n 18 22 26 23 49 104 LS Mean (SE) 13.17 (2.06) 13.46 (1.91) 15.72 (1.80) 16.03 (1.89) 15.77 (1.25) 14.5 (8.5) VBSI n 20 22 29 24 53 104 LS Mean (SE) 4.46 (0.59) 4.25 (0.57) 5.31 (0.54) 4.36 (0.55) 4.85 (0.35) 4.43 (3.17) LHBSI n 21 22 29 24 53 104 LS Mean (SE) 0.136 (0.020) 0.119 (0.020) 0.186 (0.018) 0.191 (0.019) 0.188 (0.013) 0.340 (0.190) RHBSI n 21 22 29 24 53 LS Mean (SE) 0.135 (0.020) 0.110 (0.020) 0.176 (0.018) 0.171 (0.019) 0.173 (0.013)

Regional distribution of fibrillar amyloid deposition in the brain as a function of CSF beta-amyloid 1-42 and biomarkers of neurodegeneration

polygenetic profilewas predictive of age of AD diagnosis, AD vs control, and MCI conversion to AD over a three-year period. It was alsoweakly correlated to cognitive performance as measured by the modified ADAS-Cog and MMSE scores. As previously shown, imaging data is highly predictive of AD vs control and MCI conversion; we also show that it is correlated to age of AD diagnosis and cognitive performance. When imaging and genetic information is combined, all predictivemeasures improve (Tables 3& 4). Predictions using a polygenetic profile suggest that most of the MCI subjects are AD-like, whichmay indicate increased risk or environmental effects that have delayed the onset ofAD (Figure 1).Conclusions:Wedemonstrate that a polygenetic profile is predictive of AD, both in terms of AD vs control and in the approximate age of AD diagnosis. When combined with imaging data, the polygenetic profile improves prediction accuracy.