Evan Fletcher, Brandon Gavett, Sarah Tomaszewski Farias, Keith Widaman, Rachel Whitmer, Audrey P Fan, Maria Corrada, Charles DeCarli, Dan Mungas
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引用次数: 0
Abstract
Introduction: Characterizing pathological changes in the brain that underlie cognitive impairment, including Alzheimer's disease and related disorders, is central to clinical concerns of prevention, diagnosis, and treatment.
Methods: We describe the properties of a brain gray matter region ("Union Signature") that is derived from four behavior-specific, data-driven signatures in a discovery cohort.
Results: In a separate validation set, the Union Signature demonstrates clinically relevant properties. Its associations with episodic memory, executive function, and Clinical Dementia Rating Sum of Boxes are stronger than those of several standardly accepted brain measures (e.g., hippocampal volume, cortical gray matter) and other previously developed brain signatures. The ability of the Union Signature to classify clinical syndromes among normal, mild cognitive impairment, and dementia exceeds that of the other measures.
Discussion: The Union Signature is a powerful, multipurpose correlate of clinically relevant outcomes and a strong classifier of clinical syndromes.
Highlights: Data-driven brain signatures are potentially valuable in models of cognitive aging.In previous work, we outlined rigorous validation of signatures for memory.This work demonstrates a signature predicting multiple clinical measures.This could be useful in models of interventions for brain support of cognition.
期刊介绍:
Alzheimer''s & Dementia: Diagnosis, Assessment & Disease Monitoring (DADM) is an open access, peer-reviewed, journal from the Alzheimer''s Association® that will publish new research that reports the discovery, development and validation of instruments, technologies, algorithms, and innovative processes. Papers will cover a range of topics interested in the early and accurate detection of individuals with memory complaints and/or among asymptomatic individuals at elevated risk for various forms of memory disorders. The expectation for published papers will be to translate fundamental knowledge about the neurobiology of the disease into practical reports that describe both the conceptual and methodological aspects of the submitted scientific inquiry. Published topics will explore the development of biomarkers, surrogate markers, and conceptual/methodological challenges. Publication priority will be given to papers that 1) describe putative surrogate markers that accurately track disease progression, 2) biomarkers that fulfill international regulatory requirements, 3) reports from large, well-characterized population-based cohorts that comprise the heterogeneity and diversity of asymptomatic individuals and 4) algorithmic development that considers multi-marker arrays (e.g., integrated-omics, genetics, biofluids, imaging, etc.) and advanced computational analytics and technologies.