A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles.

Autor: Sey NYA; UNC Neuroscience Center, University of North Carolina, Chapel Hill, NC, USA., Hu B; UNC Neuroscience Center, University of North Carolina, Chapel Hill, NC, USA.; Department of Genetics, University of North Carolina, Chapel Hill, NC, USA., Mah W; UNC Neuroscience Center, University of North Carolina, Chapel Hill, NC, USA.; Department of Genetics, University of North Carolina, Chapel Hill, NC, USA., Fauni H; UNC Neuroscience Center, University of North Carolina, Chapel Hill, NC, USA., McAfee JC; UNC Neuroscience Center, University of North Carolina, Chapel Hill, NC, USA.; Department of Genetics, University of North Carolina, Chapel Hill, NC, USA., Rajarajan P; Graduate School of Biomedical Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA.; Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA., Brennand KJ; Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.; Department of Genetics and Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA., Akbarian S; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA., Won H; UNC Neuroscience Center, University of North Carolina, Chapel Hill, NC, USA. hyejung_won@med.unc.edu.; Department of Genetics, University of North Carolina, Chapel Hill, NC, USA. hyejung_won@med.unc.edu.
Jazyk: angličtina
Zdroj: Nature neuroscience [Nat Neurosci] 2020 Apr; Vol. 23 (4), pp. 583-593. Date of Electronic Publication: 2020 Mar 09.
DOI: 10.1038/s41593-020-0603-0
Abstrakt: Most risk variants for brain disorders identified by genome-wide association studies reside in the noncoding genome, which makes deciphering biological mechanisms difficult. A commonly used tool, multimarker analysis of genomic annotation (MAGMA), addresses this issue by aggregating single nucleotide polymorphism associations to nearest genes. Here we developed a platform, Hi-C-coupled MAGMA (H-MAGMA), that advances MAGMA by incorporating chromatin interaction profiles from human brain tissue across two developmental epochs and two brain cell types. By analyzing gene regulatory relationships in the disease-relevant tissue, H-MAGMA identified neurobiologically relevant target genes. We applied H-MAGMA to five psychiatric disorders and four neurodegenerative disorders to interrogate biological pathways, developmental windows and cell types implicated for each disorder. Psychiatric-disorder risk genes tended to be expressed during mid-gestation and in excitatory neurons, whereas neurodegenerative-disorder risk genes showed increasing expression over time and more diverse cell-type specificities. H-MAGMA adds to existing analytic frameworks to help identify the neurobiological principles of brain disorders.
Databáze: MEDLINE
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