NINDS Human Genetics Resource Center

National Institute of Neurological Disorders and Stroke

The National Institute of Neurological Disorders and Stroke is committed to gene discovery, as a strategy for identifying the genetic causes and correlates of nervous system disorders. The NINDS Human Genetics Resource Center banks samples donated by individuals with cerebrovascular disease, dystonia, epilepsy, motor neuron disease, Parkinsonism and Tourette Syndrome, as well as population controls

Available samples 


New Cerebrovascular Disease Samples Available!

More than 1000 DNA samples from the REasons for Geographic and Racial Differences in Stroke (REGARDS) project  have been added to the NINDS Human Genetics Resource Center and are available through the catalog to the scientific community. Since 2003, REGARDS, a NINDS funded project, has worked to better understand geographic and ethnic contributions to risk of stroke.


  • Aug 2021

    Diverse genetic causes of polymicrogyria with epilepsy

    This study performed trio-based whole exome sequencing (WES) in a multicenter, international cohort of patients with polymicrogyria and epilepsy recruited and extensively phenotyped through the Epilepsy Phenome/Genome Project (EPGP) and sequenced through the Epi4K Consortium.

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  • Feb 2021

    Evolution of a Human-Specific Tandem Repeat Associated with ALS

    In this study, published in The American Journal of Human Genetics, researchers took a genome-wide approach to look for human-specific repeat variants, variable number tandem repeats (VNTRs), that distinguish neurological disease populations.

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  • Aug 2020

    Kv1.3 modulates neuroinflammation and neurodegeneration in Parkinson’s disease

    In this study, published in The Journal of Clinical Investigation, researchers used NINDS Repository lymphoblastoid cell lines to investigate the role of microglial Kv1.3, a voltage-gated potassium channel, in Parkinson’s Disease (PD) pathology and the transcriptional and posttranslational modifications of this channel in PD models.

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