Browsing by Author "Nosheny, Rachel"

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    Increasing participant diversity in AD research: Plans for digital screening, blood testing, and a community-engaged approach in the Alzheimer's Disease Neuroimaging Initiative 4
    (Wiley, 2023) Weiner, Michael W.; Veitch, Dallas P.; Miller, Melanie J.; Aisen, Paul S.; Albala, Bruce; Beckett, Laurel A.; Green, Robert C.; Harvey, Danielle; Jack, Clifford R., Jr.; Jagust, William; Landau, Susan M.; Morris, John C.; Nosheny, Rachel; Okonkwo, Ozioma C.; Perrin, Richard J.; Petersen, Ronald C.; Rivera-Mindt, Monica; Saykin, Andrew J.; Shaw, Leslie M.; Toga, Arthur W.; Tosun, Duygu; Trojanowski, John Q.; Alzheimer's Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of Medicine
    Introduction: The Alzheimer's Disease Neuroimaging Initiative (ADNI) aims to validate biomarkers for Alzheimer's disease (AD) clinical trials. To improve generalizability, ADNI4 aims to enroll 50-60% of its new participants from underrepresented populations (URPs) using new biofluid and digital technologies. ADNI4 has received funding from the National Institute on Aging beginning September 2022. Methods: ADNI4 will recruit URPs using community-engaged approaches. An online portal will screen 20,000 participants, 4000 of whom (50-60% URPs) will be tested for plasma biomarkers and APOE. From this, 500 new participants will undergo in-clinic assessment joining 500 ADNI3 rollover participants. Remaining participants (∼3500) will undergo longitudinal plasma and digital cognitive testing. ADNI4 will add MRI sequences and new PET tracers. Project 1 will optimize biomarkers in AD clinical trials. Results and discussion: ADNI4 will improve generalizability of results, use remote digital and blood screening, and continue providing longitudinal clinical, biomarker, and autopsy data to investigators.
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    Overview of Alzheimer's Disease Neuroimaging Initiative and future clinical trials
    (Wiley, 2025) Weiner, Michael W.; Kanoria, Shaveta; Miller, Melanie J.; Aisen, Paul S.; Beckett, Laurel A.; Conti, Catherine; Diaz, Adam; Flenniken, Derek; Green, Robert C.; Harvey, Danielle J.; Jack, Clifford R., Jr.; Jagust, William; Lee, Edward B.; Morris, John C.; Nho, Kwangsik; Nosheny, Rachel; Okonkwo, Ozioma C.; Perrin, Richard J.; Petersen, Ronald C.; Rivera-Mindt, Monica; Saykin, Andrew J.; Shaw, Leslie M.; Toga, Arthur W.; Tosun, Duygu; Veitch, Dallas P.; Alzheimer's Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of Medicine
    The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to optimize and validate biomarkers for clinical trials while sharing all data and biofluid samples with the global scientific community. ADNI has been instrumental in standardizing and validating amyloid beta (Aβ) and tau positron emission tomography (PET) imaging. ADNI data were used for the US Food and Drug Administration (FDA) approval of the Fujirebio and Roche Elecsys cerebrospinal fluid diagnostic tests. Additionally, ADNI provided data for the trials of the FDA-approved treatments aducanumab, lecanemab, and donanemab. More than 6000 scientific papers have been published using ADNI data, reflecting ADNI's promotion of open science and data sharing. Despite its enormous success, ADNI has some limitations, particularly in generalizing its data and findings to the entire US/Canadian population. This introduction provides a historical overview of ADNI and highlights its significant accomplishments and future vision to pioneer "the clinical trial of the future" focusing on demographic inclusivity. HIGHLIGHTS: The Alzheimer's Disease Neuroimaging Initiative (ADNI) introduced a novel model for public-private partnerships and data sharing. It successfully validated amyloid and Tau PET imaging, as well as CSF and plasma biomarkers, for diagnosing Alzheimer's disease. ADNI generated and disseminated vital data for designing AD clinical trials.
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    The Alzheimer's Disease Neuroimaging Initiative in the era of Alzheimer's disease treatment: A review of ADNI studies from 2021 to 2022
    (Wiley, 2024) Veitch, Dallas P.; Weiner, Michael W.; Miller, Melanie; Aisen, Paul S.; Ashford, Miriam A.; Beckett, Laurel A.; Green, Robert C.; Harvey, Danielle; Jack, Clifford R., Jr.; Jagust, William; Landau, Susan M.; Morris, John C.; Nho, Kwangsik T.; Nosheny, Rachel; Okonkwo, Ozioma; Perrin, Richard J.; Petersen, Ronald C.; Rivera Mindt, Monica; Saykin, Andrew; Shaw, Leslie M.; Toga, Arthur W.; Tosun, Duygu; Alzheimer’s Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of Medicine
    The Alzheimer's Disease Neuroimaging Initiative (ADNI) aims to improve Alzheimer's disease (AD) clinical trials. Since 2006, ADNI has shared clinical, neuroimaging, and cognitive data, and biofluid samples. We used conventional search methods to identify 1459 publications from 2021 to 2022 using ADNI data/samples and reviewed 291 impactful studies. This review details how ADNI studies improved disease progression understanding and clinical trial efficiency. Advances in subject selection, detection of treatment effects, harmonization, and modeling improved clinical trials and plasma biomarkers like phosphorylated tau showed promise for clinical use. Biomarkers of amyloid beta, tau, neurodegeneration, inflammation, and others were prognostic with individualized prediction algorithms available online. Studies supported the amyloid cascade, emphasized the importance of neuroinflammation, and detailed widespread heterogeneity in disease, linked to genetic and vascular risk, co-pathologies, sex, and resilience. Biological subtypes were consistently observed. Generalizability of ADNI results is limited by lack of cohort diversity, an issue ADNI-4 aims to address by enrolling a diverse cohort.
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    The Alzheimer's Disease Neuroimaging Initiative-4 (ADNI-4) Engagement Core: A culturally informed, community-engaged research (CI-CER) model to advance brain health equity
    (Wiley, 2024) Rivera Mindt, Mónica; Arentoft, Alyssa; Calcetas, Amanda T.; Guzman, Vanessa A.; Amaza, Hannatu; Ajayi, Adeyinka; Ashford, Miriam T.; Ayo, Omobolanle; Barnes, Lisa L.; Camuy, Alicia; Conti, Catherine; Diaz, Adam; Easter, Bashir; Gonzalez, David J.; Graham Dotson, Yolanda; Hoang, Isabella; Germano, Kaori Kubo; Maestre, Gladys E.; Magaña, Fabiola; Meyer, Oanh L.; Miller, Melanie J.; Nosheny, Rachel; Ta Park, Van M.; Parkins, Shaniya; Renier Thomas, Lisa; Strong, Joe; Talavera, Sandra; Verney, Steven P.; Weisensel, Trinity; Weiner, Michael W.; Okonkwo, Ozioma C.; Alzheimer's Disease Neuroimaging Initiative; Medicine, School of Medicine
    Introduction: The Alzheimer's Disease Neuroimaging Initiative-4 (ADNI-4) Engagement Core was launched to advance Alzheimer's disease (AD) and AD-related dementia (ADRD) health equity research in underrepresented populations (URPs). We describe our evidence-based, scalable culturally informed, community-engaged research (CI-CER) model and demonstrate its preliminary success in increasing URP enrollment. Methods: URPs include ethnoculturally minoritized, lower education (≤ 12 years), and rural populations. The CI-CER model includes: (1) culturally informed methodology (e.g., less restrictive inclusion/exclusion criteria, sociocultural measures, financial compensation, results disclosure, Spanish Language Capacity Workgroup) and (2) inclusive engagement methods (e.g., the Engagement Core team; Hub Sites; Community-Science Partnership Board). Results: As of April 2024, 60% of ADNI-4 new in-clinic enrollees were from ethnoculturally or educationally URPs. This exceeds ADNI-4's ≥ 50% URP representation goal for new enrollees but may not represent final enrollment. Discussion: Findings show a CI-CER model increases URP enrollment in AD/ADRD clinical research and has important implications for clinical trials to advance health equity. Highlights: The Alzheimer's Disease Neuroimaging Initiative-4 (ADNI-4) uses a culturally informed, community-engaged research (CI-CER) approach. The CI-CER approach is scalable and sustainable for broad, multisite implementation. ADNI-4 is currently exceeding its inclusion goals for underrepresented populations.