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Recent developments of PET amyloid ligands have made it possible to visualize the presence of Aβ deposition in the brain of living participants and to assess the consequences especially in individuals with no objective sign of cognitive deficits. The present review will focus on amyloid imaging in cognitively normal elderly, asymptomatic at-risk populations, and individuals with subjective cognitive decline. It will cover the prevalence of amyloid-positive cases amongst cognitively normal elderly, the influence of risk factors for AD, the relationships to cognition, atrophy and prognosis, longitudinal amyloid imaging and ethical aspects related to amyloid imaging in cognitively normal individuals. Almost ten years of research have led to a few consensual and relatively consistent findings: some cognitively normal elderly have Aβ deposition in their brain, the prevalence of amyloid-positive cases increases in at-risk populations, the prognosis for these individuals is worse than for those with no Aβ deposition, and significant increase in Aβ deposition over time is detectable in cognitively normal elderly. More inconsistent findings are still under debate; these include the relationship between Aβ deposition and cognition and brain volume, the sequence and cause-to-effect relations between the different AD biomarkers, and the individual outcome associated with an amyloid positive versus negative scan. Preclinical amyloid imaging also raises important ethical issues. While amyloid imaging is definitely useful to understand the role of Aβ in early stages, to define at-risk populations for research or for clinical trial, and to assess the effects of anti-amyloid treatments, we are not ready yet to translate research results into clinical practice and policy. More researches are needed to determine which information to disclose from an individual amyloid imaging scan, the way of disclosing such information and the impact on individuals and on society.

In early Alzheimer's disease (AD), the hippocampal region is the area most severely affected by cellular and structural alterations, yet glucose hypometabolism predominates in the posterior association cortex and posterior cingulate gyrus. One prevalent hypothesis to account for this discrepancy is that posterior cingulate hypometabolism results from disconnection from the hippocampus through disruption of the cingulum bundle. However, only partial and indirect evidence currently supports this hypothesis. Thus, using structural magnetic resonance imaging and 2-[ 18 F]fluoro-2-deoxy-D-glucose positron emission tomography in 18 patients with early AD, we assessed the relationships between hippocampal atrophy, white matter integrity, and gray matter metabolism by means of a whole-brain voxel-based correlative approach. We found that hippocampal atrophy is specifically related to cingulum bundle disruption, which is in turn highly correlated to hypometabolism of the posterior cingulate cortex but also of the middle cingulate gyrus, thalamus, mammillary bodies, parahippocampal gyrus, and hippocampus (all part of Papez's circuit), as well as the right temporoparietal associative cortex. These results provide the first direct evidence supporting the disconnection hypothesis as a major factor contributing to the early posterior hypometabolism in AD. Disruption of the cingulum bundle also appears to relate to hypometabolism in a large connected network over and above the posterior cingulate cortex, encompassing the whole memory circuit of Papez (consistent with the key location of this white matter tract within this loop) and also, but indirectly, the right posterior association cortex.

Aim The aim of this paper is to describe the clinical features of COVID‐19‐related encephalopathy and their metabolic correlates using brain 2‐desoxy‐2‐fluoro‐D‐glucose (FDG)‐positron‐emission tomography (PET)/computed tomography (CT) imaging. Background and purpose A variety of neurological manifestations have been reported in association with COVID‐19. COVID‐19‐related encephalopathy has seldom been reported and studied. Methods We report four cases of COVID‐19‐related encephalopathy. The diagnosis was made in patients with confirmed COVID‐19 who presented with new‐onset cognitive disturbances, central focal neurological signs, or seizures. All patients underwent cognitive screening, brain magnetic resonance imaging (MRI), lumbar puncture, and brain 2‐desoxy‐2‐fluoro‐D‐glucose (FDG)‐positron‐emission tomography (PET)/computed tomography (CT) (FDG‐PET/CT). Results The four patients were aged 60 years or older, and presented with various degrees of cognitive impairment, with predominant frontal lobe impairment. Two patients presented with cerebellar syndrome, one patient had myoclonus, one had psychiatric manifestations, and one had status epilepticus. The delay between first COVID‐19 symptoms and onset of neurological symptoms was between 0 and 12 days. None of the patients had MRI features of encephalitis nor significant cerebrospinal fluid (CSF) abnormalities. SARS‐CoV‐2 RT‐PCR in the CSF was negative for all patients. All patients presented with a consistent brain FDG‐PET/CT pattern of abnormalities, namely frontal hypometabolism and cerebellar hypermetabolism. All patients improved after immunotherapy. Conclusions Despite varied clinical presentations, all patients presented with a consistent FDG‐PET pattern, which may reflect an immune mechanism.

Hippocampal atrophy, posterior cingulate and frontal glucose hypometabolism, and white-matter tract disruption are well described early macroscopic events in Alzheimer's disease. The relationships between these three types of alterations have been documented in previous studies, but their chronology still remains to be established. The present study used multi-modal fluorodeoxyglucose-positron emission tomography and magnetic resonance imaging longitudinal data to address this question in patients with amnestic mild cognitive impairment. We found unidirectional, specific sequential relationships between: (i) baseline hippocampal atrophy and both cingulum bundle (r = 0.70; P = 3 × 10⁻³) and uncinate fasciculus (r = 0.75; P = 7 × 10⁻⁴) rate of atrophy; (ii) baseline cingulum bundle atrophy and rate of decline of posterior (r = 0.72; P = 2 × 10⁻³); and anterior (r = 0.74; P = 1 × 10⁻³) cingulate metabolism; and (iii) baseline uncinate white matter atrophy and subgenual metabolism rate of change (r = 0.65; P = 6 × 10⁻³). Baseline local grey matter atrophy was not found to contribute to hypometabolism progression within the posterior and anterior cingulate as well as subgenual cortices. These findings suggest that hippocampal atrophy progressively leads to disruption of the cingulum bundle and uncinate fasciculus, which in turn leads to glucose hypometabolism of the cingulate and subgenual cortices, respectively. This study reinforces the relevance of remote mechanisms above local interactions to account for the pattern of metabolic brain alteration observed in amnestic mild cognitive impairment, and provides new avenues to assess the sequence of events in complex diseases characterized by multiple manifestations.

Amyloid-β deposition in Alzheimer's disease is thought to start while individuals are still cognitively unimpaired and it is hypothesized that after an early phase of fast accumulation, a plateau is reached by the time of cognitive decline. However, few longitudinal Pittsburgh compound B-positron emission tomography studies have tested this hypothesis, and with conflicting results. The purpose of this work is to further our understanding of the dynamics of amyloid-β deposition in a large longitudinal cohort. A total of 32 patients with Alzheimer's disease, 49 subjects with mild cognitive impairment and 103 healthy controls underwent two Pittsburgh compound B-positron emission tomography scans 18 months apart. For each participant, a parametric map of Pittsburgh compound B-positron emission tomography rate of change was created [(follow-up scan - baseline scan)/follow-up duration] and entered in a voxelwise three-way analysis of covariance, with clinical status (healthy controls, mild cognitive impairment or Alzheimer's disease), disease progression (clinical conversion from healthy controls to mild cognitive impairment or Alzheimer's disease, or from mild cognitive impairment to Alzheimer's disease) and Pittsburgh compound B status (positive versus negative) as independent factors. Only a significant effect of the Pittsburgh compound B status was found: both Pittsburgh compound B-positive and -negative subjects showed a significant increase in amyloid-β deposition, with this increase being significantly higher in Pittsburgh compound B-positive individuals. This finding suggests either that Pittsburgh compound B-negative individuals have slower rates of amyloid-β accumulation than positive, or that the proportion of individuals showing significant increase in amyloid-β deposition, termed 'Pittsburgh compound B accumulators', is higher within the Pittsburgh compound B-positive group than within the Pittsburgh compound B-negative group. The bimodal distribution of the individual rates of neocortical amyloid-β accumulation observed support the existence of 'Pittsburgh compound B non-accumulators' and 'Pittsburgh compound B accumulators' and different clustering analyses led to a consistent threshold to separate these two subgroups (0.014-0.022 standardized uptake value ratio(pons)/year). The voxelwise three-way analysis of covariance was thus recomputed with the 'Pittsburgh compound B accumulators' only and the results were almost unchanged, with the Pittsburgh compound B-positive group showing higher accumulation than the Pittsburgh compound B-negative group. Finally, a significant negative correlation was found between Pittsburgh compound B rate of change and Pittsburgh compound B baseline burden, but only in the Pittsburgh compound B-positive group (r= -0.24; P=0.025). Higher rates of amyloid-β deposition are associated with higher amyloid-β burden suggesting that amyloid-β deposition does not reach a plateau when cognitive impairments manifest but is instead an ongoing process present even at the Alzheimer's dise...

Recent advances in neuroimaging have highlighted the interest to differentiate hippocampal subfields for cognitive neurosciences and more notably in assessing the effects of normal and pathological aging. The main goal of the present study is to investigate the effects of normal aging onto the volume of the different hippocampal subfields. For this purpose, we developed a new magnetic resonance sequence together with reliable tracing guidelines to assess the volume of different subfields of the hippocampus using a 3 Tesla scanner, and estimated the validity of a simpler and less time-consuming method based on the widely-used automatic Voxel-Based Morphometry (VBM) technique. Three hippocampal regions of interest were delineated on the right and left hippocampi of 50 healthy subjects between 18 and 68 years old corresponding to the CA1, subiculum and other (including CA2-3-4 and Dentate Gyrus) subfields. A strong effect of age was found on the volume of the subiculum only, with a decrease paralleling that of the global gray matter volume, while CA1 and other subfields seemed relatively spared. Although less precise than the ROI-tracing technique, the VBM-based method appeared as a reliable alternative especially to distinguish CA1 and subiculum subfields. Our findings of a specific effect of age on the subiculum are consistent with the developmental hypothesis ("last-in first-out" theory). This contrasts with the predominant vulnerability of the CA1 subfield to Alzheimer's disease reported in several previous studies, suggesting that the assessment of hippocampal subfields may improve the discrimination between normal and pathological aging.

The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of systems dysfunction within distinct molecular, cellular and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an “omics”-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND. The goals are to identify common biological denominators or differentiating classifiers across the continuum of ND during detectable stages of pathophysiological progression, characterize systems-based intermediate endophenotypes, validate multi-modal novel diagnostic systems biomarkers, and advance clinical intervention trial designs by utilizing systems-based intermediate endophenotypes and candidate surrogate markers. Achieving these goals is key to the ultimate development of early and effective individualized treatment of ND, such as Alzheimer’s disease (AD). The Alzheimer Precision Medicine Initiative (APMI) and cohort program (APMI-CP), as well as the Paris based core of the Sorbonne University Clinical Research Group “Alzheimer Precision Medicine” (GRC-APM) were recently launched to facilitate the passageway from conventional clinical diagnostic and drug development towards breakthrough innovation based on the investigation of the comprehensive biological nature of aging individuals. The APMI movement is gaining momentum to systematically apply both systems neurophysiology and systems biology in exploratory translational neuroscience research on ND.