Alzheimer's disease (AD) affects more than 5 million Americans, and this number is expected to nearly triple to more than 13 million by 2050 due to the growing population of older adults in our society. In Veterans, the overall prevalence of dementia among those treated at VA medical centers has been estimated at 7.3%. AD is the most common cause of dementia in Veterans aged 65 and older. Veterans may be at increased risk for AD relative to the general population due to the demographics of the Veteran population (e.g., older age) and the high prevalence of cardiovascular risk factors (e.g., hypertension, diabetes) which can increase risk for cognitive decline and dementia. As the number of Veterans diagnosed with AD increases dramatically in the coming years and decades, the costs associated with dementia care will also rise at alarming rates. The process of AD is believed to begin many years prior to the clinical diagnosis, and there is a need for enhanced detection and characterization of early phases of AD (i.e., mild cognitive impairment [MCI]). Previous studies have shown that AD and MCI are heterogeneous disorders that involve multiple underlying neuropathologies, including coexisting AD and cerebrovascular disease pathologies. Although there has been an increased focus on identifying sophisticated biomarkers indicative of early AD, methods of characterizing cognition in prodromal AD have remained relatively coarse. It has recently been established that the conventional method of diagnosing MCI is highly susceptible to diagnostic errors, while a novel actuarial neuropsychological method for MCI diagnosis significantly improves diagnostic accuracy. The goal of this Career Development Award (CDA-2) is for the candidate to develop the necessary skills to become an independent clinical scientist investigating cognitive and biomarker profiles associated with prodromal AD in Veterans. The application contains a research project aimed at identifying accurate and inaccurate MCI diagnoses in 84 older adult Veterans and characterizing participants in terms of their unique vascular and AD biomarker profiles. [The project will also examine preclinical AD, an asymptomatic phase of AD in which individuals are classified as cognitively normal yet test positive for biomarkers/cognitive markers associated with AD.] All participants will undergo a multimodal assessment at baseline and repeat neuropsychological evaluation at one-year intervals. Vascular biomarkers will include cerebrospinal fluid (CSF) markers of blood-brain barrier breakdown (i.e., cyclophilin A, matrix metalloproteinase 9, and a CSF/plasma albumin quotient ratio), and neuroimaging evidence of vascular pathology (i.e., white matter hyperintensities, cerebral microbleeds, reduced cerebral blood flow). AD biomarkers will include CSF concentrations of beta-amyloid, tau, and hyperphosphorylated tau, and neuroimaging markers of cortical thinning. This study is highly innovative in that it is the first to examine vascular and AD biomarkers of both accurate and inaccurate diagnosis using novel definitional criteria for MCI in a Veteran population. [The use of actuarial criteria to define subtle cognitive decline using individual test scores in preclinica AD is also novel.] This CDA-2 application includes a comprehensive training program which builds upon the applicant's background and existing skills in neuropsychological assessment/diagnosis, cognitive aging, and cognitive profiles of MCI. The training plan is focused on building additional competencies in CSF and neuroimaging biomarkers associated with vascular and AD risks, longitudinal data analysis, and developing expertise in the integration of neuropsychology and biomarkers. The multidisciplinary mentoring team includes expertise in all aspects of the proposal including cognitive profiling of MCI, CSF biomarkers, neuroimaging biomarkers, and longitudinal statistics. The proposed project and the exceptional training opportunities available at the VA San Diego Healthcare System and the University of California San Diego will assist the applicant in accomplishing her long-term career objective of transitioning into an independent VA clinical scientist conducting patient-oriented research in the field of neuropsychology and dementia risk.

Public Health Relevance

The proposed project aims to identify accurate and inaccurate MCI diagnoses using novel diagnostic criteria, and to investigate the cognitive and biomarker profiles of MCI [and 'preclinical' AD] in a Veteran population. Previous research has shown that MCI is inaccurately diagnosed in a large percentage (i.e., one third) of MCI cohorts in most research studies and clinical trials; thus, the novel method of diagnosing MCI seeks to shift current research and clinical practice paradigms. This line of research will contribute to Veterans' healthcare by 1) improving MCI diagnosis by reducing false positive and false negative diagnostic errors, [2) identifying very early or 'preclinical' signs of AD], 3) improving the ability to identify individuls at risk for progression to Alzheimer's disease (AD), which will ultimately allow for treatment strategies to be implemented at an earlier stage, and 4) providing information about distinct etiologies or underlying mechanisms of the disease.

Agency
National Institute of Health (NIH)
Institute
Veterans Affairs (VA)
Type
Veterans Administration (IK2)
Project #
5IK2CX001415-02
Application #
9378733
Study Section
Neurobiology D (NURD)
Project Start
2016-10-01
Project End
2021-09-30
Budget Start
2017-10-01
Budget End
2018-09-30
Support Year
2
Fiscal Year
2018
Total Cost
Indirect Cost
Name
VA San Diego Healthcare System
Department
Type
DUNS #
073358855
City
San Diego
State
CA
Country
United States
Zip Code
92161
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Bangen, Katherine J; Werhane, Madeleine L; Weigand, Alexandra J et al. (2018) Reduced Regional Cerebral Blood Flow Relates to Poorer Cognition in Older Adults With Type 2 Diabetes. Front Aging Neurosci 10:270
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Bondi, Mark W; Edmonds, Emily C; Salmon, David P (2017) Alzheimer's Disease: Past, Present, and Future. J Int Neuropsychol Soc 23:818-831