Single-cell epigenomic identification of inherited risk loci in Alzheimer's and Parkinson's disease

Genome-wide association studies (GWAS) 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. To this end, we present a multi-omic epigenetic atlas of the adult hum...

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Vydáno v:bioRxiv
Hlavní autoři: M Ryan Corces, Shcherbina, Anna, Kundu, Soumya, Gloudemans, Michael J, Fresard, Laure, Granja, Jeffrey M, Louie, Bryan H, Shams, Shadi, Bagdatli, S Tansu, Maxwell Robert Mumbach, Liu, Bosh, Montine, Kathleen S, Greenleaf, William J, Kundaje, Anshul, Montgomery, Stephen B, Chang, Howard Y, Montine, Thomas J
Médium: Paper
Jazyk:angličtina
Vydáno: Cold Spring Harbor Cold Spring Harbor Laboratory Press 06.01.2020
Cold Spring Harbor Laboratory
Vydání:1.1
Témata:
Alzheimer's disease
Brain
Chromatin
Epigenetics
Genome-wide association studies
Genomes
Genomics
Haplotypes
Learning algorithms
Microglia
Movement disorders
Neurodegenerative diseases
Non-coding RNA
Oligodendrocytes
Parkinson's disease
Phenotypes
Regulatory sequences
Single-nucleotide polymorphism
Tau protein
ISSN:2692-8205, 2692-8205
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Shrnutí:Genome-wide association studies (GWAS) 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. To this end, we present a multi-omic epigenetic atlas of the adult human brain through profiling of the chromatin accessibility landscapes and three-dimensional chromatin interactions of seven brain regions across a cohort of 39 cognitively healthy individuals. Single-cell chromatin accessibility profiling of 70,631 cells from six of these brain regions identifies 24 distinct cell clusters and 359,022 cell type-specific regulatory elements, capturing the regulatory diversity of the adult brain. We develop a machine learning classifier to integrate this multi-omic framework and predict dozens of functional single nucleotide polymorphisms (SNPs), nominating gene and cellular targets for previously orphaned GWAS loci. These predictions both inform well-studied disease-relevant genes, such as BIN1 in microglia for Alzheimer's disease (AD) and reveal novel gene-disease associations, such as STAB1 in microglia and MAL in oligodendrocytes for Parkinson's disease (PD). Moreover, we dissect the complex inverted haplotype of the MAPT (encoding tau) PD risk locus, identifying ectopic enhancer-gene contacts in neurons that increase MAPT expression and may mediate this disease association. This work greatly expands our understanding of inherited variation in AD and PD and provides a roadmap for the epigenomic dissection of noncoding regulatory variation in disease.
Bibliografie:SourceType-Working Papers-1
ObjectType-Working Paper/Pre-Print-1
content type line 50
ISSN:2692-8205
2692-8205
DOI:10.1101/2020.01.06.896159