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JARLIFE Vol 13, 2024

ASSOCIATION BETWEEN MODIFIABLE RISK FACTORS AND LEVELS OF BLOOD-BASED BIOMARKERS OF ALZHEIMER’S AND RELATED DEMENTIAS IN THE LOOK AHEAD COHORT

K.M. Hayden, M.M. Mielke, J.K. Evans, R. Neiberg, D. Molina-Henry, M. Culkin, S. Marcovina, K.C. Johnson, O.T. Carmichael, S.R. Rapp, B.C. Sachs, J. Ding, H. Shappell, L. Wagenknecht, J.A. Luchsinger, M.A. Espeland

J Aging Res & Lifestyle 2024;13:1-21

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BACKGROUND: Emerging evidence suggests that a number of factors can influence blood-based biomarker levels for Alzheimer’s disease (AD) and Alzheimer’s related dementias (ADRD). We examined the associations that demographic and clinical characteristics have with AD/ADRD blood-based biomarker levels in an observational continuation of a clinical trial cohort of older individuals with type 2 diabetes and overweight or obesity. METHODS: Participants aged 45-76 years were randomized to a 10-year Intensive Lifestyle Intervention (ILI) or a diabetes support and education (DSE) condition. Stored baseline and end of intervention (8-13 years later) plasma samples were analyzed with the Quanterix Simoa HD-X Analyzer. Changes in Aβ42, Aβ40, Aβ42/Aβ40, ptau181, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) were evaluated in relation to randomization status, demographic, and clinical characteristics. RESULTS: In a sample of 779 participants from the Look AHEAD cohort, we found significant associations between blood-based biomarkers for AD/ADRD and 15 of 18 demographic (age, gender, race and ethnicity, education) and clinical characteristics (APOE, depression, alcohol use, smoking, body mass index, HbA1c, diabetes duration, diabetes treatment, estimated glomerular filtration rate, hypertension, and history of cardiovascular disease) . CONCLUSIONS: Blood-based biomarkers of AD/ADRD are influenced by common demographic and clinical characteristics. These factors should be considered carefully when interpreting these AD/ADRD blood biomarker values for clinical or research purposes.

CITATION:
K.M. Hayden ; M.M. Mielke ; J.K. Evans ; R. Neiberg ; D. Molina-Henry ; M. Culkin ; S. Marcovina ; K.C. Johnson ; O.T. Carmichael ; S.R. Rapp ; B.C. Sachs ; J. Ding ; H. Shappell ; L. Wagenknecht ; J.A. Luchsinger ; M.A. Espeland (2024): Association between Modifiable Risk Factors and Levels of Blood-Based Biomarkers of Alzheimer’s and Related Dementias in the Look AHEAD Cohort. The Journal of Aging and Lifestyle (JARLife). http://dx.doi.org/10.14283/jarlife.2024.1

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ELLIQ, AN AI-DRIVEN SOCIAL ROBOT TO ALLEVIATE LONELINESS: PROGRESS AND LESSONS LEARNED

E. Broadbent, K. Loveys, G. Ilan, G. Chen, M.M. Chilukuri, S.G. Boardman, P.M. Doraiswamy, D. Skuler

J Aging Res & Lifestyle 2024;13:22-28

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BACKGROUND: Loneliness is a significant issue in older adults and can increase the risk of morbidity and mortality. OBJECTIVE: To present the development of ElliQ, a proactive, AI-driven social robot with multiple social and health coaching functions specifically designed to address loneliness and support older people. DEVELOPMENT/IMPLEMENTATION: ElliQ, a consumer robot with a friendly appearance, uses voice, sounds, light, and buttons through a touch screen to facilitate conversation, music, video calls, well-being assessments, stress reduction, cognitive games, and health reminders. The robot was deployed by 15 government agencies in the USA. Initial experience suggests it is not only highly engaging for older people but may be able to improve their quality of life and reduce loneliness. In addition, the development of a weekly report that patients can share with their clinicians to allow better integration into routine care is described. CONCLUSION: This paper describes the development and real-world implementation of this product innovation and discusses challenges encountered and future directions.

CITATION:
E. Broadbent ; K. Loveys ; G. Ilan ; G. Chen ; M.M. Chilukuri ; S.G. Boardman ; P.M. Doraiswamy ; D. Skuler (2024): ElliQ, an AI-Driven Social Robot to Alleviate Loneliness: Progress and Lessons Learned. The Journal of Aging and Lifestyle (JARLife). http://dx.doi.org/10.14283/jarlife.2024.2

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