A nation-wide initiative for brain imaging and clinical phenotype data federation in Swiss university memory centres

Amnestic Syndrome in Memory Clinics: Similar Morphological Brain Patterns in Older Adults with and without Alzheimer's Disease

Background

Amnestic syndrome of the hippocampal type (ASHT) in Memory Clinics is a presentation common to Alzheimer's disease (AD). However, ASHT can be found in other neurodegenerative disorders.

Objective

To compare brain morphometry including hippocampal volumes between amnestic older adults with and without AD pathology and investigate their relationship with memory performance and cerebrospinal fluid (CSF) biomarkers.

Methods

Brain morphometry of 92 consecutive patients (72.5±6.8 years old; 39% female) with Free and Cued Selective Recall Reminding Test (FCSRT) total recall < 40/48 was assessed with an automated algorithm and compared between AD and non-AD patients, as defined by CSF biomarkers.

Results

AD and non-AD patients presented comparable brain morphology. Total recall was associated to hippocampal volume irrespectively from AD pathology.

Conclusions

Brain morphometry, including hippocampal volumes, is similar between AD and non-AD older adults with ASHT evaluated in a Memory Clinic, underlying the importance of using molecular biomarkers for the diagnosis of AD.

Medical Informatics Platform (MIP): A Pilot Study Across Clinical Italian Cohorts

Introduction: With the shift of research focus to personalized medicine in Alzheimer's Dementia (AD), there is an urgent need for tools that are capable of quantifying a patient's risk using diagnostic biomarkers. The Medical Informatics Platform (MIP) is a distributed e-infrastructure federating large amounts of data coupled with machine-learning (ML) algorithms and statistical models to define the biological signature of the disease. The present study assessed (i) the accuracy of two ML algorithms, i.e., supervised Gradient Boosting (GB) and semi-unsupervised 3C strategy (Categorize, Cluster, Classify-CCC) implemented in the MIP and (ii) their contribution over the standard diagnostic workup. Methods: We examined individuals coming from the MIP installed across 3 Italian memory clinics, including subjects with Normal Cognition (CN, n = 432), Mild Cognitive Impairment (MCI, n = 456), and AD (n = 451). The GB classifier was applied to best discriminate the three diagnostic classes in 1,339 subjects, and the CCC strategy was used to refine the classical disease categories. Four dementia experts provided their diagnostic confidence (DC) of MCI conversion on an independent cohort of 38 patients. DC was based on clinical, neuropsychological, CSF, and structural MRI information and again with addition of the outcome from the MIP tools. Results: The GB algorithm provided a classification accuracy of 85% in a nested 10-fold cross-validation for CN vs. MCI vs. AD discrimination. Accuracy increased to 95% in the holdout validation, with the omission of each Italian clinical cohort out in turn. CCC identified five homogeneous clusters of subjects and 36 biomarkers that represented the disease fingerprint. In the DC assessment, CCC defined six clusters in the MCI population used to train the algorithm and 29 biomarkers to improve patients staging. GB and CCC showed a significant impact, evaluated as +5.99% of increment on physicians' DC. The influence of MIP on DC was rated from "slight" to "significant" in 80% of the cases. Discussion: GB provided fair results in classification of CN, MCI, and AD. CCC identified homogeneous and promising classes of subjects via its semi-unsupervised approach. We measured the effect of the MIP on the physician's DC. Our results pave the way for the establishment of a new paradigm for ML discrimination of patients who will or will not convert to AD, a clinical priority for neurology.

Precision prevention of Alzheimer's and other dementias: Anticipating future needs in the control of risk factors and implementation of disease-modifying therapies

Empirical evidence suggests that a fair proportion of dementia cases are preventable, that some preventive actions can be taken immediately, and others may soon be implemented. Primary prevention may target cognitively normal persons with modifiable risk factors through lifestyle and multiple domain interventions (including general cardiovascular health). While the effect on individuals may be modest, it might have a large societal impact by decreasing overall dementia incidence by up to 35%. Secondary prevention will target cognitively normal persons at high risk of dementia due to Alzheimer's disease pathology with future anti-amyloid, anti-tau, or other drugs. This approach is likely to have major benefits to both individuals and society. Memory clinics will need structural and functional changes to adapt to novel technologies and increased patients' demands, and brand-new services may need to be developed with specific skills on risk profiling, risk communication, and personalized risk reduction plans.