Search

Despite an ever-expanding number of analytics with the potential to impact clinical care, the field currently lacks point-of-care technological tools that allow clinicians to efficiently select disease-relevant data about their patients, algorithmically derive clinical indices (eg, risk scores), and view these data in straightforward graphical formats to inform real-time clinical decisions. Thus far, solutions to this problem have relied on either bottom-up approaches that are limited to a single clinic or generic top-down approaches that do not address clinical users' specific setting-relevant or disease-relevant needs. As a road map for developing similar platforms, we describe our experience with building a custom but institution-wide platform that enables economies of time, cost, and expertise. The BRIDGE platform was designed to be modular and scalable and was customized to data types relevant to given clinical contexts within a major university medical center. The development process occurred by using a series of human-centered design phases with extensive, consistent stakeholder input. This institution-wide approach yielded a unified, carefully regulated, cross-specialty clinical research platform that can be launched during a patient's electronic health record encounter. The platform pulls clinical data from the electronic health record (Epic; Epic Systems) as well as other clinical and research sources in real time; analyzes the combined data to derive clinical indices; and displays them in simple, clinician-designed visual formats specific to each disorder and clinic. By integrating an application into the clinical workflow and allowing clinicians to access data sources that would otherwise be cumbersome to assemble, view, and manipulate, institution-wide platforms represent an alternative approach to achieving the vision of true personalized medicine., (©Riley Bove, Erica Schleimer, Paul Sukhanov, Michael Gilson, Sindy M Law, Andrew Barnecut, Bruce L Miller, Stephen L Hauser, Stephan J Sanders, Katherine P Rankin. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 15.02.2022.)

Background/objectives: Brief cognitive screens lack the sensitivity to detect mild cognitive impairment (MCI) or support differential diagnoses. The objective of this study was to validate the 10-minute, tablet-based University of California, San Francisco (UCSF) Brain Health Assessment (BHA) to overcome these limitations., Design: Cross-sectional., Setting: UCSF Memory and Aging Center., Participants: Older adults (N = 347) (neurologically healthy controls (n = 185), and individuals diagnosed with MCI (n = 99), dementia (n = 42), and as normal with concerns (n = 21))., Measurements: The BHA includes subtests of memory, executive function and speed, visuospatial skills, and language and an optional informant survey. Participants completed the Montreal Cognitive Assessment (MoCA) and criterion-standard neuropsychological tests. Standardized structural 3T brain magnetic resonance imaging was performed in 145 participants., Results: At a fixed 85% specificity rate, the BHA had 100% sensitivity to dementia and 84% to MCI; the MoCA had 75% sensitivity to dementia and 25% to MCI. The BHA had 83% sensitivity to MCI likely due to AD and 88% to MCI unlikely due to AD, and the MoCA had 58% sensitivity to MCI likely AD and 24% to MCI unlikely AD. The BHA subtests demonstrated moderate to high correlations with the criterion-standard tests from their respective cognitive domains. Memory test performance correlated with medial temporal lobe volumes; executive and speed with frontal, parietal, and basal ganglia volumes; and visuospatial with right parietal volumes., Conclusion: The BHA had excellent combined sensitivity and specificity to detect dementia and MCI, including MCI due to diverse etiologies. The subtests provide efficient, valid measures of neurocognition that are critical in making a differential diagnosis., (© 2018, Copyright the Authors Journal compilation © 2018, The American Geriatrics Society.)

Background: Alzheimer disease (AD) is a progressive disorder that affects cognitive function. There is increasing support for the role of neuroinflammation and aberrant immune regulation in the pathophysiology of AD. The immunoregulatory human leukocyte antigen (HLA) complex has been linked to susceptibility for a number of neurodegenerative diseases, including AD; however, studies to date have failed to consistently identify a risk HLA haplotype for AD. Contributing to this difficulty are the complex genetic organization of the HLA region, differences in sequencing and allelic imputation methods, and diversity across ethnic populations., Methods and Findings: Building on prior work linking the HLA to AD, we used a robust imputation method on two separate case-control cohorts to examine the relationship between HLA haplotypes and AD risk in 309 individuals (191 AD, 118 cognitively normal [CN] controls) from the San Francisco-based University of California, San Francisco (UCSF) Memory and Aging Center (collected between 1999-2015) and 11,381 individuals (5,728 AD, 5,653 CN controls) from the Alzheimer's Disease Genetics Consortium (ADGC), a National Institute on Aging (NIA)-funded national data repository (reflecting samples collected between 1984-2012). We also examined cerebrospinal fluid (CSF) biomarker measures for patients seen between 2005-2007 and longitudinal cognitive data from the Alzheimer's Disease Neuroimaging Initiative (n = 346, mean follow-up 3.15 ± 2.04 y in AD individuals) to assess the clinical relevance of identified risk haplotypes. The strongest association with AD risk occurred with major histocompatibility complex (MHC) haplotype A*03:01~B*07:02~DRB1*15:01~DQA1*01:02~DQB1*06:02 (p = 9.6 x 10-4, odds ratio [OR] [95% confidence interval] = 1.21 [1.08-1.37]) in the combined UCSF + ADGC cohort. Secondary analysis suggested that this effect may be driven primarily by individuals who are negative for the established AD genetic risk factor, apolipoprotein E (APOE) ɛ4. Separate analyses of class I and II haplotypes further supported the role of class I haplotype A*03:01~B*07:02 (p = 0.03, OR = 1.11 [1.01-1.23]) and class II haplotype DRB1*15:01- DQA1*01:02- DQB1*06:02 (DR15) (p = 0.03, OR = 1.08 [1.01-1.15]) as risk factors for AD. We followed up these findings in the clinical dataset representing the spectrum of cognitively normal controls, individuals with mild cognitive impairment, and individuals with AD to assess their relevance to disease. Carrying A*03:01~B*07:02 was associated with higher CSF amyloid levels (p = 0.03, β ± standard error = 47.19 ± 21.78). We also found a dose-dependent association between the DR15 haplotype and greater rates of cognitive decline (greater impairment on the 11-item Alzheimer's Disease Assessment Scale cognitive subscale [ADAS11] over time [p = 0.03, β ± standard error = 0.7 ± 0.3]; worse forgetting score on the Rey Auditory Verbal Learning Test (RAVLT) over time [p = 0.02, β ± standard error = -0.2 ± 0.06]). In a subset of the same cohort, dose of DR15 was also associated with higher baseline levels of chemokine CC-4, a biomarker of inflammation (p = 0.005, β ± standard error = 0.08 ± 0.03). The main study limitations are that the results represent only individuals of European-ancestry and clinically diagnosed individuals, and that our study used imputed genotypes for a subset of HLA genes., Conclusions: We provide evidence that variation in the HLA locus-including risk haplotype DR15-contributes to AD risk. DR15 has also been associated with multiple sclerosis, and its component alleles have been implicated in Parkinson disease and narcolepsy. Our findings thus raise the possibility that DR15-associated mechanisms may contribute to pan-neuronal disease vulnerability.

Purpose: To describe the results of efforts to recruit Asian Americans into longitudinal research on cognitive decline in aging., Design and Methods: Recruitment strategies include clinics for assessment of cognitive impairment at the University of California, San Francisco campus and San Francisco's Chinatown, lectures to local health care providers and community members, participation in community events, and publications in mass media., Results: Over 200 Chinese patients were evaluated in our outreach clinic. Many were primarily Chinese speaking with low levels of education. One hundred and twenty-five participants enrolled, and annual follow-up has been 88%. Among enrollees, 36% were recruited from our clinical service; 30% via word of mouth; and the rest from community lectures and events, flyers, and mass media. Participants who enrolled were relatively highly educated, tended to be interested in learning about their cognitive abilities, and were supportive of the goals of research., Implications: Despite the significant cultural and linguistic barriers, Chinese Americans can be successfully recruited into longitudinal studies of aging and cognitive impairment. Clinical services are a critical component of such an effort, and low education and other factors that may be associated with it are clear barriers to research participation.