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For Investigators

DEVELOPING COLLABORATIONS WITH THE BRAIN HEALTH REGISTRY (BHR)

The Brain Health Registry (BHR) is a web-based, observational research study designed to effectively capture extensive amounts of data that may enable researchers to more efficiently identify, assess, and longitudinally monitor the cognitive changes associated with the progression of neurodegenerative diseases and brain aging.

Participants in the Brain Health Registry complete online questionnaires and cognitive tests that, over time, provide researchers with valuable information and allows them to better track changes in an individual’s health, lifestyle, and cognitive function. These changes could potentially be important indicators of a person’s brain health and could help identify and recruit ideal candidates for medical research and future clinical trials. Participants may also invite a study partner, such as a family member or friend, to answer questionnaires about the participant and him/herself. This is the first large-scale neuroscience project that leverages online possibilities in this way.

By creating a large pool of pre-qualified potential participants, the Brain Health Registry can make clinical trials for neurological diagnostics and treatments faster, better, and more innovative – all of which may accelerate the discovery of effective treatments for brain disease and disorders, such as Alzheimer’s, Parkinson’s, depression, PTSD, and many more.

This study is led by Principal Investigator (PI) Rachel Nosheny,PhD, and Co-Investigators Michael Weiner, MD, and Scott Mackin, PhD. BHR is overseen by the UCSF Institutional Review Board (IRB).

CITATIONS:

  1. Weiner MW. The BrainHealthRegistry.org: Using the Internet for identification, assessment, screening, recruitment, and longitudinal monitoring of subjects for neuroscience and Alzheimer’s disease studies. J Prev Alzheimers Dis. 2014;1(2):59-61. doi:10.14283/jpad.2014.9
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  4. Insel PS, Palmqvist S, Mackin RS, et al. Assessing risk for preclinical β-amyloid pathology with APOE, cognitive, and demographic information. Alzheimers Dement (Amst). 2016;4:76-84. Published 2016 Aug 3. doi:10.1016/j.dadm.2016.07.002
  5. Mackin RS, Insel PS, Truran D, et al. Unsupervised online neuropsychological test performance for individuals with mild cognitive impairment and dementia: Results from the Brain Health Registry. Alzheimers Dement (Amst). 2018;10:573-582. Published 2018 Jun 21. doi:10.1016/j.dadm.2018.05.005
  6. Mohlenhoff BS, Insel PS, Mackin RS, et al. Total Sleep Time Interacts With Age to Predict Cognitive Performance Among Adults. J Clin Sleep Med. 2018;14(9):1587-1594. Published 2018 Sep 15. doi:10.5664/jcsm.7342
  7. Weiner MW, Nosheny R, Camacho M, et al. The Brain Health Registry: An internet-based platform for recruitment, assessment, and longitudinal monitoring of participants for neuroscience studies. Alzheimers Dement. 2018;14(8):1063-1076. doi:10.1016/j.jalz.2018.02.021
  8. Nosheny RL, Camacho MR, Insel PS, et al. Online study partner-reported cognitive decline in the Brain Health Registry. Alzheimers Dement (N Y). 2018;4:565-574. Published 2018 Oct 15. doi:10.1016/j.trci.2018.09.008
  9. Cholerton B, Weiner MW, Nosheny RL, et al. Cognitive Performance in Parkinson’s Disease in the Brain Health Registry. J Alzheimers Dis. 2019;68(3):1029-1038. doi:10.3233/JAD-181009
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  13. Ashford MT, Neuhaus J, Jin C, et al. Predicting amyloid status using self-report information from an online research and recruitment registry: The Brain Health Registry. Alzheimer’s Dement. 2020; 12:e12102. https://doi.org/10.1002/dad2.12102
  14. Alosco ML, Tripodis Y, Baucom ZH, et al. Late contributions of repetitive head impacts and TBI to depression symptoms and cognition. Neurology. 2020;95(7):e793-e804.
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  17. Nutley SK, Camacho MR, Eichenbaum J, et al. Hoarding disorder is associated with self-reported cardiovascular/metabolic dysfunction, chronic pain, and sleep apnea. J Psychiatr Res. 2021;134:15-21. doi:10.1016/j.jpsychires.2020.12.032
  18. Fockler J, Kwang W, Ashford MT, et al. Brain health registry GenePool study: A novel approach to online genetics research. Alzheimer’s Dement. 2021; 7:e12118. https://doi.org/10.1002/trc2.12118
  19. Albright J, Ashford MT, Jin C, et al. Machine learning approaches to predicting amyloid status using data from an online research and recruitment registry: The Brain Health Registry. Alzheimer’s Dement. 2021; 13:e12207. https://doi.org/10.1002/dad2.12207
  20. Mackin RS, Rhodes E, Insel PS, et al. Reliability and validity of a home-based self-administered computerized test of learning and memory using speech recognition. Aging Neuropsychol Cogn. 2022;29(5):867-881. doi:10.1080/13825585.2021.1927961
  21. Zwan MD, van der Flier WM, Cleutjens S, et al. Dutch Brain Research Registry for study participant recruitment: Design and first results. Alzheimer’s Dement. 2021; 7:e12132. https://doi.org/10.1002/trc2.12132
  22. Banh, T., Jin, C., Neuhaus, J. et al. Unsupervised Performance of the CogState Brief Battery in the Brain Health Registry: Implications for Detecting Cognitive Decline. J Prev Alzheimers Dis 9, 262–268 (2022). https://doi.org/10.14283/jpad.2021.68
  23. Nutley SK, Read M, Eichenbaum J, et al. Poor sleep quality and daytime fatigue are associated with subjective but not objective cognitive functioning in clinically relevant hoarding. Biol Psychiatry Glob Open Sci. 2022;2(4):480-488. doi:10.1016/j.bpsgos.2021.10.009
  24. Iaccarino L, La Joie R, Koeppe R, et al. rPOP: Robust PET-only processing of community acquired heterogeneous amyloid-PET data. Neuroimage. 2022;246:118775. doi:10.1016/j.neuroimage.2021.118775
  25. Howell T, Neuhaus J, Glymour MM, Weiner MW, Nosheny RL. Validity of online versus in-clinic self-reported Everyday Cognition Scale. J Prev Alzheimers Dis. 2022;9(2):269-276. doi:10.14283/jpad.2022.20
  26. Fockler J, Ashford MT, Eichenbaum J, et al. Remote blood collection from older adults in the Brain Health Registry for plasma biomarker and genetic analysis. Alzheimer’s Dement. 2022; 18: 2627–2636. https://doi.org/10.1002/alz.12617
  27. Kassam F, Chen H, Nosheny RL, et al. Cognitive profile of people with mild behavioral impairment in Brain Health Registry participants. International Psychogeriatrics. 2023;35(11):643-652. doi:10.1017/S1041610221002878
  28. Sordo Vieira L, Nguyen B, Nutley SK, et al. Self-reporting of psychiatric illness in an online patient registry is a good indicator of the existence of psychiatric illness. J Psychiatr Res. 2022;151:34-41. doi:10.1016/j.jpsychires.2022.03.022
  29. Howell T, Gummadi S, Bui C, et al. Development and implementation of an electronic Clinical Dementia Rating and Financial Capacity Instrument-Short Form. Alzheimer’s Dement. 2022; 14:e12331. https://doi.org/10.1002/dad2.12331
  30. Nutley SK, Read M, Eichenbaum J, et al. Health-related quality of life in hoarding: A comparison to chronic conditions with high disease burden. J Psychiatr Res. 2022;149:68-75. doi:10.1016/j.jpsychires.2022.02.035
  31. Ashford MT, Camacho MR, Jin C, et al. Digital culturally tailored marketing for enrolling Latino participants in a web-based registry: Baseline metrics from the Brain Health Registry. Alzheimer’s Dement. 2023; 19: 1714–1728. https://doi.org/10.1002/alz.12805
  32. Mindt MR, Okonkwo O, Weiner MW, et al. Improving generalizability and study design of Alzheimer’s disease cohort studies in the United States by including under-represented populations. Alzheimer’s Dement. 2023; 19: 1549–1557. https://doi.org/10.1002/alz.12823
  33. Sylvia L, Lunn M, Obedin-Maliver J, et al. Web-based mindfulness-based interventions for well-being: randomized comparative effectiveness trial. J Med Internet Res. 2022;24(9):e35620. doi:10.2196/35620
  34. Mackin RS, Jin C, Burns E, et al. Association of major depressive disorder with remotely administered measures of cognition and subjective report of cognitive difficulties across the adult age spectrum. J Affect Disord. 2023;326:198-205. doi:10.1016/j.jad.2022.12.045
  35. Gerstenecker A, Kennedy R, Zhang Y, et al. Item response analysis of the Financial Capacity Instrument–Short Form. Arch Clin Neuropsychol. 2023;38(5):739-758. doi:10.1093/arclin/acac112
  36. Ashford, M.T., Zhu, D., Bride, J. et al. Understanding Online Registry Facilitators and Barriers Experienced by Black Brain Health Registry Participants: The Community Engaged Digital Alzheimer’s Research (CEDAR) Study. J Prev Alzheimers Dis 10, 551–561 (2023). https://doi.org/10.14283/jpad.2023.25
  37. Mindt, M.R., Ashford, M.T., Zhu, D. et al. The Community Engaged Digital Alzheimer’s Research (CEDAR) Study: A Digital Intervention to Increase Research Participation of Black American Participants in the Brain Health Registry. J Prev Alzheimers Dis 10, 847–856 (2023). https://doi.org/10.14283/jpad.2023.32
  38. Weiner MW, Aaronson A, Eichenbaum J, et al. Brain health registry updates: An online longitudinal neuroscience platform. Alzheimer’s Dement. 2023; 19: 4935–4951. https://doi.org/10.1002/alz.13077
  39. Ashford, M.T., Eichenbaum, J., Jin, C. et al. Associations between Participant Characteristics and Participant Feedback about an Unsupervised Online Cognitive Assessment in a Research Registry. J Prev Alzheimers Dis 10, 607–614 (2023). https://doi.org/10.14283/jpad.2023.40
  40. Ashford, M.T., Aaronson, A., Kwang, W. et al. Unsupervised Online Paired Associates Learning Task from the Cambridge Neuropsychological Test Automated Battery (CANTAB®) in the Brain Health Registry. J Prev Alzheimers Dis 11, 514–524 (2024). https://doi.org/10.14283/jpad.2023.117
  41. Aaronson A, Ashford MT, Jin C, et al. Brain Health Registry Study Partner Portal: Novel infrastructure for digital, dyadic data collection. Alzheimer’s Dement. 2024; 20: 846–857. https://doi.org/10.1002/alz.13492
  42. Nosheny RL, Yen D, Howell T, et al. Evaluation of the Electronic Clinical Dementia Rating for Dementia Screening. JAMA Netw Open. 2023;6(9):e2333786. doi:10.1001/jamanetworkopen.2023.33786
  43. Nutley S, Nguyen BK, Mackin RS, et al. Relationship of Hoarding and Depression Symptoms in Older Adults. Am J Geriatr Psychiatry. 2024;32(4):497-508. doi:10.1016/j.jagp.2023.11.006
  44. Ashford MT, Jin C, Neuhaus J, et al. Participant completion of longitudinal assessments in an online cognitive aging registry: The role of medical conditions. Alzheimer’s Dement. 2024; 10:e12438. https://doi.org/10.1002/trc2.12438
  45. Young SR, Dworak EM, Novack MA, et al. Development and validation of an episodic memory measure in the Mobile Toolbox (MTB): Arranging Pictures. J Clin Exp Neuropsychol. 2024;46(4):364-373. doi:10.1080/13803395.2024.2353945
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  47. Young SR, Dworak EM, Kaat AJ, et al. Development and Validation of a Vocabulary Measure in the Mobile Toolbox. Arch Clin Neuropsychol. 2024;39(6):714-723. doi:10.1093/arclin/acae010
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COLLABORATIONS:

One of the goals of the Brain Health Registry is to assist with recruitment, assessment, and longitudinal monitoring of participants for neuroscience studies. We are eager to develop collaborations with other investigators who share the same goal of accelerating the development of improved diagnostic tests, effective treatments and preventative interventions for Alzheimer’s disease and other brain disorders.

In addition to the different methods of collaboration outlined below, we also encourage collaborators to utilize the Brain Health Registry when writing and carrying out grants. If you are interested in utilizing the Brain Health Registry in your grant, please email us at [email protected].

Brain Health Registry currently offers different methods in which we can help facilitate clinical research:

1. De-Identified Data Sharing

BHR allows and encourages sharing of the entire BHR de-identified database with qualified investigators and research teams. This is regulated by a Data Use Agreement (DUA), which requires collaborators to agree to terms including but not limited to:

  • Compliance with any rules and regulations imposed by their institution and its IRB in requesting data
  • Prohibits any attempt to identify or contact any BHR participants
  • Prohibits distribution to a 3rd party or disclosure of data beyond the uses outlined in the agreement

Learn more about De-Identified Data Sharing by clicking here

2. Co-Enrollment Programs

BHR offers the ability for collaborators to invite and track their research participants by having the research participants join BHR using a registration code. The goal of co-enrollment is to link study data collected by both research studies to create a more enriched dataset for analysis, papers and presentations, and to inform participants of future research projects.

Collaborators may opt for a modified BHR experience in which their co-enrolled participants are given a subset of questionnaires and/or cognitive tests. Communication, visit frequency, and the look and feel of the BHR experience can also be customized.

Co-enrollment programs function under both UCSF’s IRB and the Collaborator’s IRB.

Learn more about Co-Enrollment Programs by clicking here

3. Software as a Service (SaaS) Programs

*Notice: This type of collaboration is currently unavailable

BHR offers the use of its software to help collaborators run and manage their own studies. This software is available for collaborations of any type, and is run by the collaborator’s IRB. While BHR manages the software, such as backup, scaling, troubleshooting, and ongoing development, collaborators can enjoy features listed below, which will allow them to maintain control of their study.

Some features of SaaS include:

  • Personalization and custom design of domain, as well as owning the look and feel
  • Participant registration, including the ability to allow self-registration or registration by invitation only
  • Online participation consent form
  • Data collection, including the ability to view your custom study design, determine how often participants are returning, and the creation of custom automated email reminders
  • A complete Study Partner Portal, which allows study partners of participants to login and register
  • Participant communication, such as automated email reminders
  • Referral management, in which collaborators can establish and manage their own referrals to sites
  • Custom dashboards

Data collected using Brain Health Registry’s SaaS belongs to the collaborator. BHR staff does not have permission to access or use the data collected, unless explicitly granted through a Data Sharing Agreement. However, BHR can use the aggregate data for general metrics to evaluate usage and performance of the BHR platform. Additionally, individualized data may be accessed by the BHR Operations Team for the explicit purpose of debugging or troubleshooting.

4. Referral Programs

BHR offers two referral program options which are both conducted under UCSF’s IRB and the Collaborator’s IRB.

  • Comprehensive Referrals: A referral originating from the pool of participants already enrolled in BHR. These referrals have completed one or more visits containing self-report questionnaires and often cognitive tests allowing for a more comprehensive screening prior to site referral.
  • Learn more about Comprehensive Referrals by clicking here
  • Direct to Site Referral: A referral without the requirement to enroll in BHR and complete questionnaires/cognitive tests. These referrals will be referred directly to a site from either a web-based form or landing page.

Potential collaborators are encouraged to join BHR to experience the full BHR protocol.

NEXT STEPS:

If you are interested in learning more about collaborating with the Brain Health Registry, please click the “Learn More” link for the specific collaboration type you are interested in.

Personal Motivations

“

I’ve seen the impact of Alzheimer’s – I’ve had friends who have lost loved ones, and the toll is immense. So I see it as a privilege to help with medical research. I feel like this is a way I can pay it forward to future generations, including my own children.

Jackie BobergSaratoga, CA
“

There are many reasons why I'm participating in the Brain Health Registry, but here's the number one reason: my father. Ten years ago, he was diagnosed with Parkinson's disease. I want to help find a cure and participating in this project gives me the greatest opportunity to do just that.

Angela DanielsWindsor, CA
“

It’s been two years since my mom died while suffering from Alzheimer’s. I think about her every day. Participating in the Brain Health Registry is a way for me to honor her. It’s something I can do that’s real and tangible.

John FitzpatrickSan Bruno, CA
“

My godfather has Parkinson's. He's a priest, and the disease is taking away his ability to preach. I signed up with him in mind. If, in the long run, this can help save and empower voices like his, it will be a great thing. And I'd like to be a part of it.

Theresa WalshSanta Clara, CA
“

My college roommate was recently diagnosed with Parkinson's. She's working hard - exercising, meditating, doing yoga - to keep her symptoms at bay, and she's holding on to the positive attitude she's always had. I'm hoping this research can lead to a cure and help her stay positive and vital. That’s why I’m here.

Anne de la RosaSan Mateo, CA
“

PTSD doesn't have to break apart families or end lives, but it often does. Veterans like my dad who go into a war zone and come out with a devastating disorder deserve new and better treatments to help them live normal, happy and fulfilling lives. I am honored to take part in the Brain Health Registry so I might help those who have put themselves at risk in service to the nation.

Roxanna SmithOakland, CA

It’s easy to join!

(You must be 18 years or older)

1. Sign Up

You can join as an individual or with a partner.

2. Tell Us About Yourself

Answer some questions about your medical history, current health, and lifestyle.

3. Do Some Online Brain Tests

These tests exercise your memory, and are like games.