Alzheimer disease (AD) is the most common cause of dementia, with a worldwide prevalence of about 25 million in 2010, expected to be doubled by 2030 because of increased life expectancy.¹ The earliest recognizable pathological event in AD is cerebral amyloid-β aggregation.² This pathology may be present up to 20 years before the onset of dementia.^3,4 Novel research criteria for AD in individuals without dementia emphasize the presence of amyloid pathology to define the first stage of the disease.^5,6

More than 35 million people worldwide experience dementia, with Alzheimer disease (AD) hallmark pathologies amyloid-β plaques and neurofibrillary tangles as the most common cause.¹ Accurately determining the cause of dementia during life is essential to developing and implementing disease-specific therapies. However, a diagnosis based on clinical criteria alone has limited capacity to determine the histopathological cause of dementia. For example, the clinical diagnosis of probable AD shows only modest sensitivity (71%-81%) and specificity (approximately 70%) against postmortem examination,^2,3 which potentially confounds clinical trials in AD.^4,5 Development of amyloid-β–specific positron emission tomography (PET) tracers^6-9 now enable human in vivo detection of fibrillar amyloid-β in neuritic plaques. Incorporating amyloid imaging into the diagnostic workup can lead to change in diagnosis,^10-12 increased diagnostic confidence,¹¹ and altered patient management.^10,12 Approval by the US Food and Drug Administration (FDA) for [¹⁸F]florbetapir (in 2012), [¹⁸F]flutemetamol (in 2013), and [¹⁸F]florbetaben (in 2014) supports potential application of amyloid imaging in clinical practice.¹³

Gray matter atrophy, glucose hypometabolism, and β-amyloid Aβ deposition are well-described hallmarks of Alzheimer's disease, but their relationships are poorly understood. The present study aims to compare the local levels of these three alterations in humans with Alzheimer's disease. Structural magnetic resonance imaging,¹⁸F-fluorodeoxyglucose positron emission tomography (PET), and¹⁸F-florbetapir PET data from 34 amyloid-negative healthy controls and 20 demented patients with a high probability of Alzheimer's disease etiology (attested using neuroimaging biomarkers as recently recommended) were analyzed. For each patient and imaging modality, age-adjustedZ-score maps were computed, and direct between-modality voxelwise comparison and correlation analyses were performed. Significant differences in the levels of atrophy, hypometabolism, and Aβ deposition were found in most brain areas, but the hierarchy differed across regions. A cluster analysis revealed distinct subsets of regions: (1) in the hippocampus, atrophy exceeded hypometabolism, whereas Aβ load was minimal; (2) in posterior association areas, Aβ deposition was predominant, together with high hypometabolism and lower but still significant atrophy; and (3) in frontal regions, Aβ deposition was maximal, whereas structural and metabolic alterations were low. Atrophy and hypometabolism significantly correlated in the hippocampus and temporo-parietal cortex, whereas Aβ load was not significantly related to either atrophy or hypometabolism. These findings provide direct evidence for regional variations in the hierarchy and relationships between Aβ load, hypometabolism, and atrophy. Altogether, these variations probably reflect the differential involvement of region-specific pathological or protective mechanisms, such as the presence of neurofibrillary tangles, disconnection, as well as compensation processes.

Background/Aims: The aim of this study was to identify neuropsychiatric subsyndromes of the Neuropsychiatric Inventory in a large sample of outpatients with Alzheimer’s disease (AD). Methods: Cross-sectional data of 2,354 patients with AD from 12 centres from the European Alzheimer’s Disease Consortium were collected. Principal component analysis was used for factor analysis. Results: The results showed the presence of 4 neuropsychiatric subsyndromes: hyperactivity, psychosis, affective symptoms and apathy. The subsyndrome apathy was the most common, occurring in almost 65% of the patients. Conclusion: This large study has provided additional robust evidence for the existence of neuropsychiatric subsyndromes in AD.

Major depressive disorder is a debilitating disease. Unfortunately, treatment with antidepressants (ADs) has limited therapeutic efficacy since resistance to AD is common. Research in this field is hampered by the lack of a reliable natural animal model of AD resistance. Depression resistance is related to various factors, including the attendance of cardiovascular risk factors and past depressive episodes. We aimed to design a rodent model of depression resistance to ADs, associating cardiovascular risk factors with repeated unpredicted chronic mild stress (UCMS). Male BALB/c mice were given either a regular (4% fat) or a high fat diet (45% fat) and subjected to two 7-week periods of UCMS separated by 6 weeks. From the second week of each UCMS procedure, vehicle or fluoxetine (10 mg/kg, i.p.) was administrated daily. The effects of the UCMS and fluoxetine in both diet conditions were assessed using physical (coat state and body weight) and behavioural tests (the reward maze test and the splash test). The results demonstrate that during the second procedure, UCMS induced behavioural changes, including coat state degradation, disturbances in self-care behaviour (splash test) and anhedonia (reward maze test) and these were reversed by fluoxetine in the regular diet condition. In contrast, the high-fat diet regimen prevented the AD fluoxetine from abolishing the UCMS-induced changes. In conclusion, by associating UCMS—an already validated animal model of depression—with high-fat diet regimen, we designed a naturalistic animal model of AD resistance related to a sub-nosographic clinical entity of depression.