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Single-cell epigenomic analyses implicate candidate causal variants at inherited risk loci for Alzheimer’s and Parkinson’s diseases

Genome-wide association studies (GWAS) of neurological diseases have identified thousands of variants associated with disease phenotypes. However, the majority of these variants do not alter coding sequences, making it difficult to assign their function. Here, we present a multi-omic epigenetic atla...

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Detalles Bibliográficos
Autores principales: Corces, M. Ryan, Shcherbina, Anna, Kundu, Soumya, Gloudemans, Michael J., Frésard, Laure, Granja, Jeffrey M., Louie, Bryan H., Eulalio, Tiffany, Shams, Shadi, Bagdatli, S. Tansu, Mumbach, Maxwell R., Liu, Boxiang, Montine, Kathleen S., Greenleaf, William J., Kundaje, Anshul, Montgomery, Stephen B., Chang, Howard Y., Montine, Thomas J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7606627/
https://www.ncbi.nlm.nih.gov/pubmed/33106633
http://dx.doi.org/10.1038/s41588-020-00721-x
Descripción
Sumario:Genome-wide association studies (GWAS) of neurological diseases have identified thousands of variants associated with disease phenotypes. However, the majority of these variants do not alter coding sequences, making it difficult to assign their function. Here, we present a multi-omic epigenetic atlas of the adult human brain through profiling of single-cell chromatin accessibility landscapes and three-dimensional (3D) chromatin interactions of diverse adult brain regions across a cohort of cognitively healthy individuals. We developed a machine-learning classifier to integrate this multi-omic framework and predict dozens of functional single-nucleotide polymorphisms (SNPs) for Alzheimer’s disease (AD) and Parkinson’s disease (PD), nominating target genes and cell types for previously orphaned GWAS loci. Moreover, we dissected the complex inverted haplotype of the MAPT (encoding tau) PD risk locus, identifying putative ectopic regulatory interactions in neurons that may mediate this disease association. This work expands our understanding of inherited variation and provides a roadmap for the epigenomic dissection of causal regulatory variation in disease.