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Alzheimer’s Disease (AD)
Unlearn’s AD DTG was trained and tested based on data obtained from multiple sources. The text below acknowledges data contributions from certain providers.
Data used in preparation of this project were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found here. The ADNI was launched in 2003 as a public-private partnership, led by Principal Investigator Michael W. Weiner, MD. The primary goal of ADNI has been to test whether serial magnetic resonance imaging (MRI), positron emission tomography (PET), other biological markers, and clinical and neuropsychological assessment can be combined to measure the progression of mild cognitive impairment (MCI) and early Alzheimer’s disease (AD). For up-to-date information, see www.adni-info.org. Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for NeuroImaging at the University of Southern California.
Data used in the preparation of this project were obtained from the Critical Path for Alzheimer’s Disease (CPAD) Database. As such, the investigators within CPAD contributed to the design and implementation of the CPAD database and/or provided data, but did not participate in the analysis of the data or the writing of this report. In 2008, Critical Path Institute, in collaboration with the Engelberg Center for Health Care Reform at the Brookings Institution, formed the Coalition Against Major Diseases (rebranded to Critical Path for Alzheimer’s Disease (CPAD) consortium in 2018). The consortium brings together patient groups, biopharmaceutical companies, and scientists from academia, the U.S. Food and Drug Administration (FDA), the European Medicines Agency (EMA), the National Institute of Neurological Disorders and Stroke (NINDS), and the National Institute on Aging (NIA). The Critical Path for Alzheimer’s Disease (CPAD) consortium includes over 200 scientists from member and non-member organizations. The data available in the CPAD database has been volunteered by CPAD member companies and non-member organizations.
Data used in preparation of this project were obtained from the National Alzheimer’s Coordinating Center (NACC). The NACC database is funded by NIA/NIH Grant U24 AG072122. NACC data are contributed by the NIA-funded ADCs: P50 AG005131 (PI James Brewer, MD, PhD); P50 AG005133 (PI Oscar Lopez, MD); P50 AG005134 (PI Bradley Hyman, MD, PhD); P50 AG005136 (PI Thomas Grabowski, MD); P50 AG005138 (PI Mary Sano, PhD); P50 AG005142 (PI Helena Chui, MD); P50 AG005146 (PI Marilyn Albert, PhD); P50 AG005681 (PI John Morris, MD); P30 AG008017 (PI Jeffrey Kaye, MD); P30 AG008051 (PI Thomas Wisniewski, MD); P50 AG008702 (PI Scott Small, MD); P30 AG010124 (PI John Trojanowski, MD, PhD); P30 AG010129 (PI Charles DeCarli, MD); P30 AG010133 (PI Andrew Saykin, PsyD); P30 AG010161 (PI David Bennett, MD); P30 AG012300 (PI Roger Rosenberg, MD); P30 AG013846 (PI Neil Kowall, MD); P30 AG013854 (PI Robert Vassar, PhD); P50 AG016573 (PI Frank LaFerla, PhD); P50 AG016574 (PI Ronald Petersen, MD, PhD); P30 AG019610 (PI Eric Reiman, MD); P50 AG023501 (PI Bruce Miller, MD); P50 AG025688 (PI Allan Levey, MD, PhD); P30 AG028383 (PI Linda Van Eldik, PhD); P50 AG033514 (PI Sanjay Asthana, MD, FRCP); P30 AG035982 (PI Russell Swerdlow, MD); P50 AG047266 (PI Todd Golde, MD, PhD); P50 AG047270 (PI Stephen Strittmatter, MD, PhD); P50 AG047366 (PI Victor Henderson, MD, MS); P30 AG049638 (PI Suzanne Craft, PhD); P30 AG053760 (PI Henry Paulson, MD, PhD); P30 AG066546 (PI Sudha Seshadri, MD); P20 AG068024 (PI Erik Roberson, MD, PhD); P20 AG068053 (PI Marwan Sabbagh, MD); P20 AG068077 (PI Gary Rosenberg, MD); P20 AG068082 (PI Angela Jefferson, PhD); P30 AG072958 (PI Heather Whitson, MD); P30 AG072959 (PI James Leverenz, MD).
Data used in preparation of this project were obtained from the Longitudinal Cohort Study (LCS), delivered by the European Prevention of Alzheimer’s Disease (EPAD) Consortium. As such investigators within the EPAD LCS and EPAD Consortium contributed to the design and implementation of EPAD and/or provided data but did not participate in analysis or writing of this report. A complete list of EPAD Investigators can be found here. EPAD LCS is registered at www.clinicaltrials.gov Identifier: NCT02804789. Data used in preparation of this article were obtained from the EPAD LCS data set V.IMI, doi:10.34688/epadlcs_v.imi_20.10.30. The EPAD LCS was launched in 2015 as a public-private partnership, led by Chief Investigator Professor Craig Ritchie MB BS. The primary research goal of the EPAD LCS is to provide a well-phenotyped probability-spectrum population for developing and continuously improving disease models for Alzheimer’s disease in individuals without dementia. This work used data and/or samples from the EPAD project which received support from the EU/EFPIA Innovative Medicines Initiative Joint Undertaking EPAD grant agreement n° 115736 and an Alzheimer’s Association Grant (SG-21-818099-EPAD).
Data were also provided in part by OASIS-4: Clinical Cohort: Principal Investigators: T. Benzinger, L. Koenig, P. LaMontagne. https://doi.org/10.1016/j.nicl.2020.102248
Data used in preparation of this research were obtained from the University of California, San Diego Alzheimer’s Disease Cooperative Study (ADCS) (National Institute on Aging Grant Number U19AG010483). Consequently, the ADCS Core Directors contributed to the design and implementation of the ADCS and/or provided data but did not participate in analysis or writing of this report.
Amyotrophic Lateral Sclerosis (ALS)
Unlearn’s ALS DTG was trained and tested based on data obtained from multiple sources. The text below acknowledges data contributions from certain providers.
Data used in the preparation of this project were obtained from the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) Database. As such, the following organizations and individuals within the PRO-ACT Consortium contributed to the design and implementation of the PRO-ACT Database and/or provided data, but did not participate in the analysis of the data or the writing of this report: ALS Therapy Alliance, Cytokinetics, Inc., Amylyx Pharmaceuticals, Inc., Knopp Biosciences, Neuraltus Pharmaceuticals, Inc., Neurological Clinical Research Institute, MGH; Northeast ALS Consortium; Novartis; Prize4Life Israel; Regeneron Pharmaceuticals, Inc.; Sanofi; Teva Pharmaceutical Industries, Ltd., The ALS Association. In 2011, Prize4Life, in collaboration with the Northeast ALS Consortium, and with funding from the ALS Therapy Alliance, formed the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) Consortium. The data available in the PRO-ACT Database has been volunteered by PRO-ACT Consortium members.
We acknowledge the NEALS Biorepository for providing all or part of the biofluids from the ALS, healthy controls and non-ALS neurological controls used in this study.
Data used in the preparation of this project were obtained from Witzel S, Frauhammer F, Steinacker P, Devos D, Pradat PF, Meininger V, Halbgebauer S, Oeckl P, Schuster J, Anders S, Dorst J, Otto M, Ludolph AC. Neurofilament light and heterogeneity of disease progression in amyotrophic lateral sclerosis: development and validation of a prediction model to improve interventional trials. Transl Neurodegener. 2021 Aug 26;10(1):31. doi: 10.1186/s40035-021-00257-y. PMID: 34433481; PMCID: PMC8390195. Creative Commons license: https://creativecommons.org/licenses/by/4.0/
Data used in the preparation of this article were obtained from The Pooled Resource Open-Access Clinical Research (PRO-ACE) Database. The data available in the PRO-ACE Database have been volunteered by PRO-ACE Consortium members.
Data used in the preparation of this article were obtained from the National Institute of Neurological Disorders and Stroke (NINDS) Database.
Cudkowicz ME, Titus S, Kearney M, Yu H, Sherman A, Schoenfeld D, Hayden D, Shui A, Brooks B, Conwit R, Felsenstein D, Greenblatt DJ, Keroack M, Kissel JT, Miller R, Rosenfeld J, Rothstein JD, Simpson E, Tolkoff-Rubin N, Zinman L, Shefner JM; Ceftriaxone Study Investigators. Safety and efficacy of ceftriaxone for amyotrophic lateral sclerosis: a multi-stage, randomised, double-blind, placebo-controlled trial. Lancet Neurol. 2014 Nov;13(11):1083-1091. doi: 10.1016/S1474-4422(14)70222-4. Epub 2014 Oct 5. PMID: 25297012; PMCID: PMC4216315.
Atopic Dermatitis (AtD)
Data used in this indication do not require acknowledgements.
Crohn’s Disease (CD)
Unlearn’s CD DTG was trained and tested based on data obtained from the IBD Plexus program of the Crohn’s & Colitis Foundation.
Dyslipidemia (DLD)
Unlearn’s DLD DTG was trained and tested based on data from the ALLHAT, BARI2D, GHCoE-New Delhi, ICARE, LRC-CCPT, MEDFOCUS, MRFIT, POWERUP, PROMISE, and SNAP studies. Research Materials were obtained from the NHLBI Biologic Specimen and Data Repository Information Coordinating Center and do not necessarily reflect the opinions or views of the aforementioned studies.
Frontotemporal Dementia (FTD)
Unlearn’s FTD DTG was trained and tested based on data obtained from multiple sources. The text below acknowledges data contributions from certain providers.
Data used in preparation of this project were obtained from the National Alzheimer’s Coordinating Center (NACC). The NACC database is funded by NIA/NIH Grant U24 AG072122. NACC data are contributed by the NIA-funded ADCs: P50 AG005131 (PI James Brewer, MD, PhD); P50 AG005133 (PI Oscar Lopez, MD); P50 AG005134 (PI Bradley Hyman, MD, PhD); P50 AG005136 (PI Thomas Grabowski, MD); P50 AG005138 (PI Mary Sano, PhD); P50 AG005142 (PI Helena Chui, MD); P50 AG005146 (PI Marilyn Albert, PhD); P50 AG005681 (PI John Morris, MD); P30 AG008017 (PI Jeffrey Kaye, MD); P30 AG008051 (PI Thomas Wisniewski, MD); P50 AG008702 (PI Scott Small, MD); P30 AG010124 (PI John Trojanowski, MD, PhD); P30 AG010129 (PI Charles DeCarli, MD); P30 AG010133 (PI Andrew Saykin, PsyD); P30 AG010161 (PI David Bennett, MD); P30 AG012300 (PI Roger Rosenberg, MD); P30 AG013846 (PI Neil Kowall, MD); P30 AG013854 (PI Robert Vassar, PhD); P50 AG016573 (PI Frank LaFerla, PhD); P50 AG016574 (PI Ronald Petersen, MD, PhD); P30 AG019610 (PI Eric Reiman, MD); P50 AG023501 (PI Bruce Miller, MD); P50 AG025688 (PI Allan Levey, MD, PhD); P30 AG028383 (PI Linda Van Eldik, PhD); P50 AG033514 (PI Sanjay Asthana, MD, FRCP); P30 AG035982 (PI Russell Swerdlow, MD); P50 AG047266 (PI Todd Golde, MD, PhD); P50 AG047270 (PI Stephen Strittmatter, MD, PhD); P50 AG047366 (PI Victor Henderson, MMarD, MS); P30 AG049638 (PI Suzanne Craft, PhD); P30 AG053760 (PI Henry Paulson, MD, PhD); P30 AG066546 (PI Sudha Seshadri, MD); P20 AG068024 (PI Erik Roberson, MD, PhD); P20 AG068053 (PI wan Sabbagh, MD); P20 AG068077 (PI Gary Rosenberg, MD); P20 AG068082 (PI Angela Jefferson, PhD); P30 AG072958 (PI Heather Whitson, MD); P30 AG072959 (PI James Leverenz, MD).
Huntington’s Disease (HD)
Unlearn’s HD DTG was trained and tested based on data obtained from multiple sources. The text below acknowledges data contributions from certain providers.
Data used in this work was generously provided by the participants in PREDICT-HD and made available by the PREDICT-HD Investigators and Coordinators of the Huntington Study Group, Jane Paulsen, Principal Investigator. PREDICT-HD was funded by the National Institute of Health (NIH) under Grant# NS040068. This work was funded by CHDI Foundation, Inc., a nonprofit biomedical research organization exclusively dedicated to developing therapeutics that will substantially improve the lives of HD-affected individuals.
Hypertension (HTN)
Unlearn’s HTN DTG was trained and tested based on data from the AIM-HIGH, ALLHAT, BARI2D, CHOICES, GHCoE-New Delhi, HHL, ICARE, IDEA, LRC-CCPT, MEDFOCUS, MRFIT, POWERUP, PROMISE, SHEP, SNAP, and TOHP studies. Research Materials were obtained from the NHLBI Biologic Specimen and Data Repository Information Coordinating Center and do not necessarily reflect the opinions or views of the aforementioned studies.
Major Depressive Disorder (MDD)
Unlearn’s MDD DTG was trained and tested based on data obtained from sources that are acknowledged below:
Data and/or research tools used in the preparation of this document were obtained from the National Institute of Mental Health (NIMH) Data Archive (NDA). NDA is a collaborative informatics system created by the National Institutes of Health to provide a national resource to support and accelerate research in mental health. Dataset identifier(s): NIMH Data Archive Collection IDs 2148, 2158, 2157, 2892, 3575, and 2199. This document reflects the views of the authors and may not reflect the opinions or views of the NIH or of the Submitters submitting original data to NDA.
Parkinson’s Disease (PD)
Unlearn’s PD DTG was trained and tested based on data obtained from multiple sources. The text below acknowledges data contributions from certain providers.
This research is based on the National Institute of Neurologic Disease and Stroke (NINDS) data received from the Archived Clinical Research Dataset website. The original study PI’s and primary study publications are acknowledged below:
Data and biospecimens used in preparation of this manuscript were obtained from the Parkinson’s Disease Biomarkers Program (PDBP) Consortium, supported by the National Institute of Neurological Disorders and Stroke at the National Institutes of Health. Investigators include: Roger Albin, Roy Alcalay, Alberto Ascherio, Thomas Beach, Sarah Berman, Bradley Boeve, F. DuBois Bowman, Shu Chen, Alice Chen-Plotkin, William Dauer, Ted Dawson, Paula Desplats, Richard Dewey, Ray Dorsey, Jori Fleisher, Kirk Frey, Douglas Galasko, James Galvin, Dwight German, Lawrence Honig, Xuemei Huang, David Irwin, Kejal Kantarci, Anumantha Kanthasamy, Daniel Kaufer, James Leverenz, Carol Lippa, Irene Litvan, Oscar Lopez, Jian Ma, Lara Mangravite, Karen Marder, Laurie Orzelius, Vladislav Petyuk, Judith Potashkin, Liana Rosenthal, Rachel Saunders-Pullman, Clemens Scherzer, Michael Schwarzschild, Tanya Simuni, Andrew Singleton, David Standaert, Debby Tsuang, David Vaillancourt, David Walt, Andrew West, Cyrus Zabetian, Jing Zhang, and Wenquan Zou. The PDBP Investigators have not participated in reviewing the data analysis or content of the manuscript.
Data used in the preparation of this article were obtained on October 2, 2023 from the Parkinson’s Progression Markers Initiative (PPMI) database (www.ppmi-info.org/access-data-specimens/download-data), RRID:SCR_006431. For up-to-date information on the study, visit www.ppmi-info.org.
Psoriasis (PsO)
Data used in this indication do not require acknowledgements.
Rheumatoid Arthritis (RA)
Data used in this indication do not require acknowledgements.
Schizophrenia (SCZ)
Unlearn’s SCZ DTG was trained and tested based on data obtained from sources that are acknowledged below:
Data and/or research tools used in the preparation of this document were obtained from the National Institute of Mental Health (NIMH) Data Archive (NDA). NDA is a collaborative informatics system created by the National Institutes of Health to provide a national resource to support and accelerate research in mental health. Dataset identifier(s): NIMH Data Archive Collection IDs 2081, 2248, and 2387. This document reflects the views of the authors and may not reflect the opinions or views of the NIH or of the Submitters submitting original data to NDA.
Stroke (STR)
Unlearn’s STR DTG was trained and tested based on data obtained from multiple sources. The text below acknowledges data contributions from certain providers.
This research is based on the National Institute of Neurologic Disease and Stroke (NINDS) data received from the Archived Clinical Research Dataset website. The original study PI’s and primary study publications are acknowledged below:
Type 2 Diabetes (T2D)
Unlearn’s T2D DTG was trained and tested based on data from the AIM-HIGH, ALLHAT, BARI2D, GHCoE-New Delhi, HHL, ICARE, MEDFOCUS, MRFIT, POWERUP, and PROMISE studies. Research Materials were obtained from the NHLBI Biologic Specimen and Data Repository Information Coordinating Center and do not necessarily reflect the opinions or views of the aforementioned studies.