Geoffroy Gagliardi

Preclinical Alzheimer's disease: A systematic review of the cohorts underlying the concept

Preclinical Alzheimers disease (AD) is a relatively recent concept describing an entity characterized by the presence of a pathophysiological biomarker signature characteristic for AD in the absence of specific clinical symptoms. There is rising interest in the scientific community to define such an early target population mainly because of failures of all recent clinical trials despite evidence of biological effects on brain amyloidosis for some compounds. A conceptual framework has recently been proposed for this preclinical phase of AD. However, few data exist on this silent stage of AD. We performed a systematic review to investigate how the concept is defined across studies. The review highlights the substantial heterogeneity concerning the three main determinants of preclinical AD: “normal cognition,” “cognitive decline,” and “AD pathophysiological signature.” We emphasize the need for a harmonized nomenclature of the preclinical AD concept and standardized population‐based and case‐control studies using unified operationalized criteria.

Cognitive and neuroimaging features and brain β-amyloidosis in individuals at risk of Alzheimer's disease (INSIGHT-preAD): a longitudinal observational study

BACKGROUND Improved understanding is needed of risk factors and markers of disease progression in preclinical Alzheimers disease. We assessed associations between brain β-amyloidosis and various cognitive and neuroimaging parameters with progression of cognitive decline in individuals with preclinical Alzheimers disease. METHODS The INSIGHT-preAD is an ongoing single-centre observational study at the Salpêtrière Hospital, Paris, France. Eligible participants were age 70-85 years with subjective memory complaints but unimpaired cognition and memory (Mini-Mental State Examination [MMSE] score ≥27, Clinical Dementia Rating score 0, and Free and Cued Selective Reminding Test [FCSRT] total recall score ≥41). We stratified participants by brain amyloid β deposition on 18F-florbetapir PET (positive or negative) at baseline. All patients underwent baseline assessments of demographic, cognitive, and psychobehavioural, characteristics, APOE ε4 allele carrier status, brain structure and function on MRI, brain glucose-metabolism on 18F-fluorodeoxyglucose (18F-FDG) PET, and event-related potentials on electroencephalograms (EEGs). Actigraphy and CSF investigations were optional. Participants were followed up with clinical, cognitive, and psychobehavioural assessments every 6 months, neuropsychological assessments, EEG, and actigraphy every 12 months, and MRI, and 18F-FDG and 18F-florbetapir PET every 24 months. We assessed associations of amyloid β deposition status with test outcomes at baseline and 24 months, and with clinical status at 30 months. Progression to prodromal Alzheimers disease was defined as an amnestic syndrome of the hippocampal type. FINDINGS From May 25, 2013, to Jan 20, 2015, we enrolled 318 participants with a mean age of 76·0 years (SD 3·5). The mean baseline MMSE score was 28·67 (SD 0·96), and the mean level of education was high (score >6 [SD 2] on a scale of 1-8, where 1=infant school and 8=higher education). 88 (28%) of 318 participants showed amyloid β deposition and the remainder did not. The amyloid β subgroups did not differ for any psychobehavioural, cognitive, actigraphy, and structural and functional neuroimaging results after adjustment for age, sex, and level of education More participants positive for amyloid β deposition had the APOE ε4 allele (33 [38%] vs 29 [13%], p<0·0001). Amyloid β1-42 concentration in CSF significantly correlated with mean 18F-florbetapir uptake at baseline (r=-0·62, p<0·0001) and the ratio of amyloid β1-42 to amyloid β1-40 (r=-0·61, p<0·0001), and identified amyloid β deposition status with high accuracy (mean area under the curve values 0·89, 95% CI 0·80-0·98 and 0·84, 0·72-0·96, respectively). No difference was seen in MMSE (28·3 [SD 2·0] vs 28·9 [1·2], p=0·16) and Clinical Dementia Rating scores (0·06 [0·2] vs 0·05 [0·3]; p=0·79) at 30 months (n=274) between participants positive or negative for amyloid β. Four participants (all positive for amyloid β deposition at baseline) progressed to prodromal Alzheimers disease. They were older than other participants positive for amyloid β deposition at baseline (mean 80·2 years [SD 4·1] vs 76·8 years [SD 3·4]) and had greater 18F-florbetapir uptake at baseline (mean standard uptake value ratio 1·46 [SD 0·16] vs 1·02 [SD 0·20]), and more were carriers of the APOE ε4 allele (three [75%] of four vs 33 [39%] of 83). They also had mild executive dysfunction at baseline (mean FCSRT free recall score 21·25 [SD 2·75] vs 29·08 [5·44] and Frontal Assessment Battery total score 13·25 [1·50] vs 16·05 [1·68]). INTERPRETATION Brain β-amyloidosis alone did not predict progression to prodromal Alzheimers disease within 30 months. Longer follow-up is needed to establish whether this finding remains consistent. FUNDING Institut Hospitalo-Universitaire and Institut du Cerveau et de la Moelle Epinière (IHU-A-ICM), Ministry of Research, Fondation Plan Alzheimer, Pfizer, and Avid.

Sex differences in functional and molecular neuroimaging biomarkers of Alzheimer's disease in cognitively normal older adults with subjective memory complaints.

Observational multimodal neuroimaging studies indicate sex differences in Alzheimers disease pathophysiological markers.

Prediction of amyloidosis from neuropsychological and MRI data for cost effective inclusion of pre-symptomatic subjects in clinical trials

We propose a method for selecting pre-symptomatic subjects likely to have amyloid plaques in the brain, based on the automatic analysis of neuropsychological and MRI data and using a cross-validated binary classifier. By avoiding systematic PET scan for selecting subjects, it reduces the cost of forming cohorts of subjects with amyloid plaques for clinical trials, by scanning fewer subjects but increasing the number of recruitments. We validate our method on three cohorts of subjects at different disease stages, and compare the performance of six classifiers, showing that the random forest yields good results more consistently, and that the method generalizes well when tested on an unseen data set.

DIFFERENCES IN SENSITIVITY TO AMYLOIDOSIS FOR STANDARD NEUROPSYCHOLOGICAL MEMORY TESTS

were administered. The levels of Ab and tau protein in the different diagnostic categories were analyzed with ANOVAs and by Tukey post-hoc tests. Multivariate regression models were computed to test whether cognitive performance was driven by the levels of amyloid load and NFT accumulation as determined by PET [F] NAV4694 and [F]MK6240. Results: The PET scans revealed that the Ab and tau protein levels were increased in AD patients (Ab 2.8360.60 SUVR; tau 3.6261.40 SUVR) compared with MCI and CH but were not different between MCI and CH. On both cognitive tests, the AD group performed worse than the MCI and the CH (p<0.001 to p1⁄40.001); the MCI performed worse than the CH on the verbal memory test (p1⁄40.029), but not on the semantic fluency test (p1⁄40.41). The regression analyses revealed that tau levels (but not Ab) were negatively linked to verbal memory (p1⁄4 0.001) and to semantic verbal fluency (p1⁄40.0002). Further analysis revealed that tau in the superior frontal lobewas associated with poor performance in semantic fluency (p1⁄40,004) and immediate recall of the logical memory task (p1⁄40.018) and tau in the hippocampus was strongly associated with poor delayed recall of the logical memory (p1⁄40.008). Conclusions: The cognitive decline was linked to tau protein but not to Ab. Furthermore, we found differential involvement of the frontal lobe and hippocampus in the cognitive performance.

THE NEURONAL COMPENSATION MODEL OF THE PRECLINICAL STAGE OF ALZHEIMER'S DISEASE: RESULTS FROM THE INSIGHT-PRE AD STUDY

N 1899 173 568 Age 55,31 (6,59) 56,46 (6,89) 57.14 (6,86) Education 13,51 (3,50) 12,38 (3,51) 13,14 (3,50) MMSE 29,09(1,04) 29,03(1,00) 28,82 (1,18) GADS Total .61 (1,35) .62 (1,24) 1,29 (2,03) % Females 64,1% 48,0% 65,0% % e4 Carriers 34,6% 37,6% 34.3,6% MBT-TPR M (SO) 24,42 (4,22) 23,19 (3.37) 23,28 (4.77) MBT-TFR M (SD) 16,94 (4,93) 15,17 (4.34) 15,53 (5.09) MBT-TDFR M (SD) 17,32 (5.0) 15,66 (4.52) 15,80 (5.43) MBT-TDPR M (SD) 24,26 (4,3) 22,94 (4.40) 23,07 (4.94) WAIS-Coding M (SD) 67,09 (14.54) 62,77 (14.63) 62,93 (14.75) WAIS-Visual Puzzles M (SD) 13,57 (4.27) 13,42 (4.32) 12,61 (4.07)

Effect of Alzheimer's disease risk and protective factors on cognitive trajectories in subjective memory complainers: An INSIGHT-preAD study

Cognitive change in people at risk of Alzheimers disease (AD) such as subjective memory complainers is highly variable across individuals.

LOW COGNITIVE AWARENESS, BUT NOT COMPLAINT, IS A GOOD MARKER OF PRECLINICAL ALZHEIMER'S DISEASE

University, Augusta, GA, USA; Northwestern University, Chicago, IL, USA; New York University-Langone Medical Center, New York City, NY, USA; Chiba University, Chiba, Japan; Gladstone Institutes, San Francisco, CA, USA; Zilkha Neurogenetic Institute, University of Southern California, Los Angeles, CA, USA; Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, M€olndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, M€olndal, Sweden; University College London, Institute of Neurology, London, United Kingdom. Contact e-mail: D.Bruno@ljmu.ac.uk

THE NEUROPSYCHOLOGICAL PROFILE OF ALZHEIMER’S DISEASE PATIENTS WITH AND WITHOUT CONFABULATIONS

Midlife Risk Factor Diabetes status NS NS p1⁄40.090 Hypertension NS NS NS BMI based Obesity p1⁄40.080 NS p1⁄40.090 CES-D 16 p1⁄40.018 NS NS Physical Exercise NS NS NS Cognitive Activities p1⁄4 0.019 NS p1⁄40.016 Summary Score p1⁄40.023 NS NS Baseline Cognitive Status 7.2 (4.3-12.0), p<.0001 IICV1⁄41 (vs 0): 7.0 (4.5-11.1), p < .0001 IICV1⁄42 or 3 (vs 0); 7.8 (4 0-15.2), p < .0001 IICV1⁄41 (vs 0): 10.2(6.3 16.5), p < .0001 IICV1⁄42 or 3 (vs 0); 24.4 (12.6-47.3), p< .0001 Longitudinal (Later) Cognitive Status 1.4(.9-2.3), p 1⁄4 .11 IICV1⁄41 (vs 0): 1.7 (1.1-2.5), p1⁄402 IICV1⁄42 or 3 (vs 0): 1.8 (3.6), p1⁄4.13 IICV-1 (vs 0); 2.2 (1.5-3.2), p< .0001 IICV1⁄42 or 3 (vs 0); 3.5 (1.8-6.8), p1⁄4.0003 (Pattern IICV Raw Score Normed Z, p1⁄4.035) (Pattern IICV – Robust Normed Z, p <.0001)

Suspected non-alzheimer disease pathophysiology (SNAP) categorization in the insight cohort

Background Suspected non-Alzheimer disease pathophysiology (SNAP) individuals are participants to studies on Alzheimer’s disease (AD) biomarkers that are considered positive for markers of neurodegeneration and negative for markers of brain amyloidosis in the absence of a major neurocognitive disorder. This concept probably encompasses numerous neurological diseases in which the mildness of symptoms is responsible for a generic term to be proposed instead of a diagnosis. Methods We categorized SNAP subjects in the INSIGHT cohort, a mono-centric French cohort at the University Salpetriere Hospital in Paris including 317 individuals with subjective cognitive decline (SCD) between 70-85 year. Standardized demographic, cognitive, MRI, 18FDG and AV45 PET imaging were performed in each subject. The SNAP population was determined based on cut-offs scores adapted from the literature. Each SNAP participant’s complete medical file was analyzed by an expert committee comprised of 3 neurologists, 1 geriatrician, 1 neuropsychologist, 1 neuroradiologist and 1 nuclear medicine MD. Diagnostic algorithms were adapted from international consensus criteria for various neurological conditions (eg Rascovsky’s criteria for Fronto-temporal dementia). Results Among the INSIGHT participants, 88 are considered amyloid (+) with a significantly increased cortical uptake of the tracer above threshold on PET imaging, and 229 are amyloid (-). The 229 amyloid negative individuals were categorized in 4 groups determined by their clinico-radiological status: Healthy control, SNAP-AD when neurodegeneration was suggestive of AD, SNAP-NONAD when the neurodegeneration was incompatible with typical AD and SNAP-MIXED in all other participants. We have then applied our diagnostic procedure in the SNAP participants to determine if this group can be divided into known neurological diseases. Conclusions This is one of the first attempts to refine the diagnostic procedure in SNAP, a frequent condition in the elderly population. Similarly to AD, a presymptomatic/early symptomatic phase of different brain affections can be diagnosed instead of using the SNAP acronym.