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January 2, 2026\",\"February 5, 2026\"],[\"January 3, 2026 - February 27, 2026\",\"April 4, 2026\"],[\"February 28, 2026 - May 1, 2026\",\"June 4, 2026\"],[\"May 2, 2026 - July 3, 2026\",\"August 6, 2026\"],[\"July 4, 2026 - August 28, 2026\",\"October 1, 2026\"],[\"August 29, 2026 - October 30, 2026\",\"December 3, 2026\"],[\"October 31, 2026 - January 1, 2027\",\"February 4, 2027\"]]",[153],"rvt-bottom-lg","Submission and Review Dates ",[],{"type":110,"tag":157,"props":158,"children":163},"accordion",{":accordions":159,"className":160},"[{\"title\":\"Review Process\",\"content\":\"\u003Cp>The BRAC committee will assess the applications based on experimental rationale, feasibility\u002Freproducibility of the assays, expertise of the investigator, availability of the institutional resources to support the study, and the statistical analysis of the number of samples required for the hypothesis testing.  Investigators will be notified by email the outcome of the review (i.e. approve, approve upon revisions, or deny) within a week after the review meeting.  Summary statements are released 2-3 weeks after review.  For applications that were ‘approved upon revisions’, investigators will be notified about concerns that would need to be addressed before the application could move forward.  Please note that the RED BRAC does not provide funding.\u003C\u002Fp>\\n\\n\u003Cp>If sample access is approved by the RED BRAC, the two possible outcomes are:\u003C\u002Fp>\\n\\n\u003Col>\\n  \u003Cli>If the study has funding, the samples are distributed to the investigator following a virtual meeting to introduce the sample distribution process (“on-boarding”) and after fulfilment by the investigator of additional requirements specified by BioSEND (i.e. MTA, Data Use Agreement, data analysis and sharing plan). For questions, please contact \u003Ca href=\\\"mailto:NINDS-HD-BRAC@ninds.nih.gov\\\">Rebecca Price, Ph.D.\u003C\u002Fa>\u003C\u002Fli> \\n\\n  \u003Cli>If the investigator has yet to obtain funding for the study, the BRAC will issue a letter to the applicant documenting provisional access to the samples requested.  This letter can be used to support an application for funding opportunities from the NIH or other organizations.  Conditional approvals will be valid for a period of up to 12 months.\u003C\u002Fli>\\n\u003C\u002Fol>\\n\\n\u003Cp>To facilitate scientific rigor and reproducibility, samples for approved applications are shipped blinded (each aliquot is labeled with a Sample ID). The BioSEND team will work with investigators during the onboarding call to create box designs to facilitate blinded analyses. Investigators must return their assay analyses into an appropriate data repository prior to being unblinded by BioSEND.\u003C\u002Fp>\\n\"}]",[161,162],"samples-accordions","als-brac",[],{"type":110,"tag":157,"props":165,"children":168},{":accordions":166,"className":167},"[{\"title\":\"RED BRAC Membership\",\"content\":\"\u003Caddress>\\n  \u003Cstrong>Fogel, Brent, MD, PhD\u003C\u002Fstrong>\u003Cbr\u002F>\\n  Associate Professor, Department of Neurology\u003Cbr\u002F>\\n  University of California Los Angeles\u003Cbr\u002F>\\n  Los Angeles, CA 90095\u003Cbr\u002F>\\n\u003C\u002Faddress>\\n\\n\u003Caddress>\\n  \u003Cstrong>Kuo, Sheng-Han, MD\u003C\u002Fstrong>\u003Cbr\u002F>\\n  Associate Professor, Department of Neurology\u003Cbr\u002F>\\n  Columbia Universityy\u003Cbr\u002F>\\n  New York, NY 10032\u003Cbr\u002F>\\n\u003C\u002Faddress>\\n\\n\u003Caddress>\\n        \u003Cstrong>Leavitt, Blair, MDCM, FRCP(C)\u003C\u002Fstrong>\u003Cbr\u002F>\\n        Professor, Medical Genetics, Centre for Molecular Medicine and Therapeutics\u003Cbr\u002F>\\n        University of British Columbia\u003Cbr\u002F>\\n        Vancouver, Canada\u003Cbr\u002F>\\n      \u003C\u002Faddress>\\n\\n\u003Caddress>\\n        \u003Cstrong>McLoughlin, Hayley, PhD\u003C\u002Fstrong>\u003Cbr\u002F>\\n        Assistant Professor, Department of Neurology\u003Cbr\u002F>\\n        University of Michigan\u003Cbr\u002F>\\n        Ann Arbor, MI 48108\u003Cbr\u002F>\\n      \u003C\u002Faddress>\\n\\n\u003Caddress>\\n        \u003Cstrong>Mouro Pinto, Ricardo, PhD, MSc\u003C\u002Fstrong>\u003Cbr\u002F>\\n        Instructor in Neurology\u003Cbr\u002F>\\n        Harvard Medical School and Massachusetts General Hospital\u003Cbr\u002F>\\n        Boston, MA 02114\u003Cbr\u002F>\\n      \u003C\u002Faddress>\\n\\n\u003Caddress>\\n        \u003Cstrong>Paulson, Henry L, MD, PhD\u003C\u002Fstrong>\u003Cbr\u002F>\\n        Professor, Department of Neurology\u003Cbr\u002F>\\n        University of Michigan\u003Cbr\u002F>\\n        Ann Arbor, MI 48109\u003Cbr\u002F>\\n      \u003C\u002Faddress>\\n\\n\u003Caddress>\\n        \u003Cstrong>Paulsen, Jane S, PhD\u003C\u002Fstrong>\u003Cbr\u002F>\\n        Professor and Vice Chair for Research, Department of Neurology\u003Cbr\u002F>\\n        University of Wisconsin-Madison\u003Cbr\u002F>\\n        Madison, WI 53705\u003Cbr\u002F>\\n      \u003C\u002Faddress>\\n\\n\u003Caddress>\\n        \u003Cstrong>Rosas, H. Diana, MD\u003C\u002Fstrong>\u003Cbr\u002F>\\n        Associate Professor, Department of Neurology\u003Cbr\u002F>\\n        Harvard Medical School\u003Cbr\u002F>\\n        Boston, MA 02114\u003Cbr\u002F>\\n      \u003C\u002Faddress>\\n\\n\u003Caddress>\\n        \u003Cstrong>Rosenthal, Liana, MD, PhD\u003C\u002Fstrong>\u003Cbr\u002F>\\n        Associate Professor, Department of Neurology\u003Cbr\u002F>\\n        Johns Hopkins University School of Medicine\u003Cbr\u002F>\\n        Baltimore, MD 21218\u003Cbr\u002F>\\n      \u003C\u002Faddress>\\n\\n\u003Caddress>\\n        \u003Cstrong>Rummey, Christian, PhD\u003C\u002Fstrong>\u003Cbr\u002F>\\n        Clinical Scientist & Statistician, Co-Founder\u003Cbr\u002F>\\n        Clinical Data Science GmbH\u003Cbr\u002F>\\n        Basel Area, Switzerland\u003Cbr\u002F>\\n      \u003C\u002Faddress>\\n\\n\u003Caddress>\\n        \u003Cstrong>Schöls, Ludger, MD\u003C\u002Fstrong>\u003Cbr\u002F>\\n        Professor, Department of Clinical Neurogenetics\u003Cbr\u002F>\\n        German Center of Neurodegenerative Diseases, University of Tübingen\u003Cbr\u002F>\\n        Tübingen, Germany\u003Cbr\u002F>\\n      \u003C\u002Faddress>\\n\\n\u003Caddress>\\n        \u003Cstrong>Schultz, Jordan, PharmD, MSCS, BCACP\u003C\u002Fstrong>\u003Cbr\u002F>\\n        Assistant Professor of Psychiatry\u003Cbr\u002F>\\n        University of Iowa\u003Cbr\u002F>\\n        Iowa City, IA 52242\u003Cbr\u002F>\\n      \u003C\u002Faddress>\\n\\n\u003Caddress>\\n        \u003Cstrong>Shakkottai, Vikram, MD, PhD\u003C\u002Fstrong>\u003Cbr\u002F>\\n        Associate Professor, Department of Neurology\u003Cbr\u002F>\\n        UT Southwestern Medical Center\u003Cbr\u002F>\\n        Dallas, TX 75390\u003Cbr\u002F>\\n      \u003C\u002Faddress>\\n\\n\u003Caddress>\\n        \u003Cstrong>Shorrock, Hannah, PhD\u003C\u002Fstrong>\u003Cbr\u002F>\\n        Assistant Professor, Department of Biological Sciences\u003Cbr\u002F>\\n        University at Albany\u003Cbr\u002F>\\n        Albany, NY 12222\u003Cbr\u002F>\\n      \u003C\u002Faddress>\\n\\n\u003Caddress>\\n        \u003Cstrong>Southwell, Amber, PhD\u003C\u002Fstrong>\u003Cbr\u002F>\\n        Associate Professor, Department Of Neuroscience\u003Cbr\u002F>\\n        University of Central Florida\u003Cbr\u002F>\\n        Orlando, FL 32827\u003Cbr\u002F>\\n      \u003C\u002Faddress>\\n\\n\u003Caddress>\\n        \u003Cstrong>Wang, Cuiling, PhD\u003C\u002Fstrong>\u003Cbr\u002F>\\n        Associate Professor, Department of Epidemiology and Population Health\u003Cbr\u002F>\\n        Albert Einstein College of Medicine\u003Cbr\u002F>\\n        The Translational Genomics Research Institute\u003Cbr\u002F>\\n        Bronx, NY 10461\u003Cbr\u002F>\\n      \u003C\u002Faddress>\\n\"}]",[161,162],[],{"type":110,"tag":141,"props":170,"children":172},{"className":171},[129],[173],{"type":110,"tag":174,"props":175,"children":176},"em",{},[177,179,189],{"type":145,"value":178},"Please note that your application will be shared with BRAC members, NINDS program staff, and BioSEND staff. Access and review of all applications is guided ethical research standards, as described in the ",{"type":110,"tag":180,"props":181,"children":186},"a",{"href":182,"className":183,"target":185},"\u002Fassets\u002Faccess-samples\u002FBRAC Confidentiality agreement 2024_508C.pdf",[184],"link","_blank",[187],{"type":145,"value":188},"Confidentiality Agreement",{"type":145,"value":190},".",{"type":145,"value":192},"  ",{"type":110,"tag":157,"props":194,"children":197},{":accordions":195,"className":196},"[{\"title\":\"Previously Approved HD Applications\",\"content\":\"\u003Ch2>Blood Levels of Soluble and Aggregated Mutant Huntingtin: Biomarkers for PreManifest Huntington's Disease Progression\u003C\u002Fh2>\\n\u003Cp>Steven Hersch, Harvard Medical School \u003C\u002Fp>\\n\u003Cp class=\\\"rvt-m-all-none\\\">Cohort: PREDICT-HD  \u003Cbr\u002F> Review Date: 2013 \u003C\u002Fp>\\n\\n\u003Cp>Abstract: Huntington’s disease (HD) is caused by the cellular expression of the toxic mutant huntingtin protein (mtHtt). Both soluble and aggregated forms of mtHtt are crucial for understanding disease progression and responses to therapeutic agents. Current assays only detect soluble protein, leaving uncertainty about interventions’ effects on aggregation. Reliable mtHtt markers that distinguish and quantify both forms are essential for understanding therapeutic impacts on pathologic processes. \u003C\u002Fp>\\n\\n\u003Ch2>Integrated Approach to Protein Biomarker Identification in Huntington’s Disease \u003C\u002Fh2>\\n\u003Cp>Howard Schulman, Caprion Proteomics US \u003C\u002Fp>\\n\u003Cp class=\\\"rvt-m-all-none\\\">Cohort: PREDICT-HD  \u003Cbr\u002F> Review Date: 2014 \u003C\u002Fp>\\n\\n\u003Cp>Abstract: This project applies mass spectrometry–based proteomic profiling to identify biomarkers for Huntington’s Disease using PREDICT-HD samples. The study compares plasma from control, early, and late progression cohorts over time to detect disease progression markers and validate them for clinical use. The ultimate goal is to develop reliable biomarkers to monitor HD progression and therapeutic effects.\u003C\u002Fp>\\n\\n\u003Ch2>A Next Generation of Biomarkers for Incipient Huntington's Disease \u003C\u002Fh2>\\n\u003Cp>Clemens Scherzer, Brigham and Women's Hospital \u003C\u002Fp>\\n\u003Cp class=\\\"rvt-m-all-none\\\">Cohort: PREDICT-HD  \u003Cbr\u002F> Review Date: 2014 \u003C\u002Fp>\\n\\n\u003Cp>Abstract: This study aims to identify microRNA and messenger RNA biomarkers that track Huntington’s Disease progression before clinical symptoms appear. Using next-generation sequencing of cerebrospinal fluid and blood samples, the study will create a biomarker platform for early detection and intervention in HD.\u003C\u002Fp>\\n\\n\u003Ch2>Metabolic Dysfunction in Huntington Disease \u003C\u002Fh2>\\n\u003Cp>Dean Jones, Emory University \u003C\u002Fp>\\n\u003Cp class=\\\"rvt-m-all-none\\\">Cohort: PREDICT-HD  \u003Cbr\u002F> Review Date: 2014 \u003C\u002Fp>\\n\\n\u003Cp>Abstract: Evidence suggests metabolic dysregulation occurs early in Huntington’s Disease. This project investigates altered metabolic pathways—including amino acid and lipid metabolism—in premanifest patients, aiming to link metabolic signatures with disease onset and progression using data from PREDICT-HD. \u003C\u002Fp>\\n\\n\u003Ch2>Interaction Between Neuroinflammation and Neurodegeneration in Huntington’s Disease \u003C\u002Fh2>\\n\u003Cp>Jason Gigley, University of Wyoming \u003C\u002Fp>\\n\u003Cp class=\\\"rvt-m-all-none\\\">Cohort: 2CARE  \u003Cbr\u002F> Review Date: 2016 \u003C\u002Fp>\\n\\n\u003Cp>Abstract: This study explores how neurotropic infection with Toxoplasma gondii influences Huntington’s Disease onset. Using patient plasma and ELISA testing, researchers will determine if seropositivity for T. gondii correlates with earlier HD onset or greater disease severity. \u003C\u002Fp>\\n\\n\u003Ch2>B-Cell Repertoire Analysis of HD Samples \u003C\u002Fh2>\\n\u003Cp>Jane Osbourn, Alchemab Therapeutics \u003C\u002Fp>\\n\u003Cp class=\\\"rvt-m-all-none\\\">Cohort: PREDICT-HD\u003Cbr\u002F> Review Date: 2023 \u003C\u002Fp>\\n\\n\u003Cp>Abstract: This collaboration applies deep B-cell repertoire analysis and proteomics to identify immune signatures associated with resilience in Huntington’s Disease. The goal is to discover antibodies or immune markers that could be developed into potential therapeutic tools. \u003C\u002Fp>\\n\\n\u003Ch2>Harmonise:HD – Influencing Huntington’s Disease Monitoring Using Multi-Study Integrated Analysis \u003C\u002Fh2>\\n\u003Cp>Lauren Byrne, University College London  \u003C\u002Fp>\\n\u003Cp class=\\\"rvt-m-all-none\\\">Cohort: PREDICT-HD\u003Cbr\u002F> Review Date: 2024\u003C\u002Fp>\\n\\n\u003Cp>Abstract: This project integrates MRI and neurofilament light (NfL) biomarker data across multiple HD cohorts to improve disease staging and monitoring. It aims to develop sensitive early-stage biomarkers and create a harmonized dataset for use in HD prevention and treatment trials.\u003C\u002Fp>\\n\\n\u003Ch2>Somatic Instability in Huntington’s Disease\u003C\u002Fh2>\\n\u003Cp>Peggy Nopoulos, University of Iowa \u003C\u002Fp>\\n\u003Cp class=\\\"rvt-m-all-none\\\">Cohort: CHANGE-HD, JOHD\u003Cbr\u002F> Review Date: 2024\u003C\u002Fp>\\n\\n\u003Cp>Abstract: This project investigates somatic instability in young HD patients using blood-derived DNA samples. Collaborating with Dr. Darren Monckton, it aims to develop accessible biomarkers for repeat expansion and understand early disease mechanisms. \u003C\u002Fp>\\n\\n\u003Ch2>Longitudinal Quantification of HTT in Circulating Brain-Derived Extracellular Vesicles \u003C\u002Fh2>\\n\u003Cp>Amber Southwell, University of Central Florida \u003C\u002Fp>\\n\u003Cp class=\\\"rvt-m-all-none\\\">Cohort: PREDICT-HD\u003Cbr\u002F> Review Date: 2025\u003C\u002Fp>\\n\\n\u003Cp>Abstract: This study measures huntingtin (HTT) protein levels in neuronal extracellular vesicles from blood, comparing them to cerebrospinal fluid levels and clinical outcomes. It aims to establish a minimally invasive biomarker for monitoring brain-derived HTT and disease progression. \u003C\u002Fp>\\n\\n\u003Ch2>A Longitudinal Metabolomic Comparison of Fast and Slow Cognitive Progression in Huntington's Disease \u003C\u002Fh2>\\n\u003Cp>Andrew McGarry, Cooper University Healthcare at Rowan University \u003C\u002Fp>\\n\u003Cp class=\\\"rvt-m-all-none\\\">Cohort: 2CARE\u003Cbr\u002F> Review Date: 2025\u003C\u002Fp>\\n\\n\u003Cp>Abstract: This longitudinal study examines plasma metabolomic profiles of HD patients with rapid or slow cognitive decline. It seeks to identify metabolic signatures linked to cognitive progression, offering insights into potential biomarkers and therapeutic targets for cognitive impairment in HD. \u003C\u002Fp>\\n\\n\"}]",[162],[],{"type":110,"tag":157,"props":199,"children":202},{":accordions":200,"className":201},"[{\"title\":\"Previously Approved SCA Applications\",\"content\":\"\u003Ch2>READISCA Biosample Access Application \\nCarrie Rubel, Biogen\u003C\u002Fh2> \\n\\n\u003Cp>Cohort: Clinical Trial Readiness for SCA1 and SCA3 (READISCA)\u003Cbr\u002F>\\nReview Date: 2020\u003C\u002Fp>\\n\\n\u003Cp>Abstract: Spinocerebellar Ataxia Type 1 (SCA1) and Spinocerebellar Ataxia Type 3 (SCA3) are rare, progressive, and fatal monogenic neurodegenerative disorders. They are caused by CAG repeat expansions that produce mutant ATXN1 or ATXN3 proteins leading to neuronal toxicity. This study aims to measure ATXN1\u002FATXN3 protein levels in CSF and plasma, assess their biological variability, and identify biomarkers of neurodegeneration relevant to disease progression and treatment response in SCA1 and SCA3.\u003C\u002Fp>\\n\\n\\n\u003Ch2>Development of Mutant ATXN1 and ATXN3 Expression Assays in CSF and Plasma\u003C\u002Fh2>\\n\u003Cp>Jaya Goyal and Neta Zach, Wave Life Sciences\u002FTakeda\u003C\u002Fp> \\n\\n\u003Cp>Cohort: Clinical Trial Readiness for SCA1 and SCA3 (READISCA)\u003Cbr\u002F>\\nReview Date: 2020\u003C\u002Fp> \\n\\n\u003Cp>Abstract: Takeda Pharmaceuticals and Wave Life Sciences are developing antisense oligonucleotide (ASO) therapies for SCA1 and SCA3. This study uses READISCA CSF and plasma samples to establish fluid biomarker assays that measure mutant ATXN1 and ATXN3 protein levels, supporting pharmacodynamic analysis and target engagement in first-in-human trials.\u003C\u002Fp>\\n\\n\\n\\n\u003Ch2>Identification of Fluid Biomarkers in Spinocerebellar Ataxia-1\u003C\u002Fh2>\\n\u003Cp>Puneet Opal, Northwestern University\u003C\u002Fp>\\n\\n\u003Cp>Cohort: Clinical Trial Readiness for SCA1 and SCA3 (READISCA)\u003Cbr\u002F> \\nReview Date: 2021\u003C\u002Fp>\\n\\n\u003Cp>Abstract: Spinocerebellar Ataxia-1 (SCA1) is a dominantly inherited neurodegenerative disorder with no current treatment. Preclinical models suggest that ATXN1-lowering therapies improve outcomes. This study seeks to validate neurofilament light chain (NFL) and ATXN1 levels in plasma and CSF as biomarkers to track disease progression and treatment efficacy.\u003C\u002Fp> \\n\\n\\n\\n\u003Ch2>Research Strategy for READISCA CSF Samples\u003C\u002Fh2> \\n\u003Cp>Abigail Collins, Ionis Pharmaceuticals\u003C\u002Fp>\\n\\n\u003Cp>Cohort: Clinical Trial Readiness for SCA1 and SCA3 (READISCA)\u003Cbr\u002F> \\nReview Date: 2021\u003C\u002Fp>\\n\\n\u003Cp>Abstract: SCA1 results from an expanded CAG repeat mutation in the ATXN1 gene. Ionis Pharmaceuticals has developed an ASO (ATXN1Rx) to reduce mutant protein levels. This study develops assays to quantify Ataxin1 concentration in CSF to monitor treatment efficacy and enable dose selection for upcoming clinical trials.\u003C\u002Fp>\\n\\n\\n\\n\u003Ch2>Circulating Protein Biomarkers of Spinocerebellar Ataxia\u003C\u002Fh2>\\n\u003Cp>Chandra Mohan, University of Houston \u003C\u002Fp>\\n\\n\u003Cp>Cohort: Clinical Trial Readiness for SCA1 and SCA3 (READISCA)\u003Cbr\u002F> \\nReview Date: 2022\u003C\u002Fp>\\n\\n\u003Cp>Abstract: This study evaluates 10 serum and plasma proteins as candidate biomarkers for SCA using ELISA validation. The analysis draws from patient cohorts in India, China, the USA, and Europe, including the READISCA cohort, to identify consistent protein signatures linked to disease severity and progression.\u003C\u002Fp>\\n\\n\\n\\n\u003Ch2>Request for CSF and Plasma Samples from SCA2 Patients to Qualify\u002FValidate Ataxin2 Expression Assays\u003C\u002Fh2>\\n\u003Cp>Aurore Sors, SERVIER \u003C\u002Fp>\\n\\n\u003Cp>Cohort: Clinical Research Consortium for the Study of Cerebellar Ataxia (CRC-SCA) \u003Cbr\u002F>\\nReview Date: 2023 \u003C\u002Fp>\\n\\n\u003Cp>Abstract: Servier is developing antisense oligonucleotide (ASO) therapy targeting ATXN2 RNA to slow SCA2 progression. This project uses CSF and plasma samples to validate Ataxin2 assays and investigate glial and axonal biomarkers to support clinical trial readiness.\u003C\u002Fp>\\n\\n\\n\\n\u003Ch2>Identifying Potential Biomarkers in SCA2 CSF\u003C\u002Fh2> \\n\u003Cp>Daniel Braas, Arrowhead Pharmaceuticals, Inc. \u003C\u002Fp>\\n\\n\u003Cp>Cohort: Clinical Research Consortium for the Study of Cerebellar Ataxia (CRC-SCA) \u003Cbr\u002F>\\nReview Date: 2024 \u003C\u002Fp>\\n\\n\u003Cp>Abstract: Arrowhead Pharmaceuticals is developing a novel therapeutic for SCA2. This study utilizes Ligand Binding Assays (LBA) and Single Molecule Counting (SMCxPRO) immunoassays to measure ATXN2 protein levels in CSF, aiming to establish biomarkers for therapeutic response and target engagement.\u003C\u002Fp> \\n\\n\\n\\n\u003Ch2>Identification of Fluid Biomarkers in Spinocerebellar Ataxia-1 \u003C\u002Fh2> \\n\u003Cp>Puneet Opal, Northwestern University Feinberg School of Medicine \u003C\u002Fp>\\n\\n\u003Cp>Cohort: Clinical Trial Readiness for SCA1 and SCA3 (READISCA) \\nReview Date: 2024 \u003C\u002Fp>\\n\\n\u003Cp>Abstract: This NIH- and NAF-funded study focuses on identifying biomarkers to improve diagnosis and monitoring of SCA1. 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