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

Abstract

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.

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Fig. 1: Schematics of the H-MAGMA approach.
Fig. 2: Spatiotemporal dynamics of brain-disorder risk genes.
Fig. 3: Cellular expression profiles of brain-disorder risk genes.
Fig. 4: Characteristics of brain-disorder risk genes.
Fig. 5: Pleiotropic genes reveal shared molecular mechanisms of psychiatric disorders.

Data availability

All GWAS summary statistics used in this study are publicly available. We deposited H-MAGMA input files derived from fetal brain and adult brain, and neuronal and astrocytic Hi-C data, and H-MAGMA output files for nine brain disorders in the GitHub repository at https://github.com/thewonlab/H-MAGMA.

Code availability

Codes used in this study are provided in the GitHub repository at https://github.com/thewonlab/H-MAGMA.

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Acknowledgements

We thank members of the Won Lab and D. H. Geschwind for helpful discussions and comments on this paper. S. Espeso Gil helped transfer Hi-C datasets for neurons and astrocytes. This research was supported by National Institute of Mental Health grants (R00MH113823 and DP2MH122403 to H.W.; R56MH101454 to K.J.B.; and R0MH106056 to S.A. and K.J.B.), a NARSAD Young Investigator Award from the Brain and Behavior Research Foundation (to H.W.), a SPARK grant from the Simons Foundation Autism Research Initiative (to H.W.), training grants from the UNC Neuroscience Center (5T32NS007431 to N.Y.A.S. and H.F.), and a Helen Lyng White Fellowship (to W.M.).

Author information

Authors and Affiliations

Authors

Contributions

H.W. designed the H-MAGMA framework. N.Y.A.S. and H.F. applied cMAGMA and H-MAGMA to nine brain disorders. J.C.M. compared H-MAGMA with cMAGMA. H.F. and W.M. performed LDSC and genetic correlation analyses. N.Y.A.S. conducted developmental trajectories analyses, RRHO and functional characterization of pleiotropic genes. B.H. analyzed astrocyte RNA sequencing data and compared H-MAGMA with eQTL-based tools. P.R., K.J.B. and S.A. contributed the Hi-C data from iPSC-derived neurons and astrocytes. N.Y.A.S. and H.W. wrote the manuscript.

Corresponding author

Correspondence to Hyejung Won.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Neuroscience thanks Nicholas Bray, Andrew Jaffe, Mina Ryten, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Comparison between H-MAGMA and cMAGMA.

a, The number and proportion of intronic and intergenic SNPs annotated to proximal and distal genes. SNPs mapped to proximal genes may also have distal associations, while SNPs mapped to distal genes do not have any association with proximal genes. b, The number of brain disorder risk genes (genes that are significantly associated with each brain disorder at a threshold of FDR<0.05) predicted by H-MAGMA and cMAGMA. % H-MAGMA denotes the percentage of H-MAGMA selective genes (genes that were identified by H-MAGMA but not by cMAGMA). c, The number of SNPs assigned to each gene for H-MAGMA and cMAGMA. Center, median; box=1st-3rd quartiles (Q); minima, Q1 - 1.5 x interquartile range (IQR); maxima, Q3 + 1.5 x IQR. d, The number and proportion of SNPs annotated to the cognate genes by H-MAGMA and cMAGMA. e, H-MAGMA selective SNPs (SNPs assigned to H-MAGMA selective genes in H-MAGMA – SNPs assigned to H-MAGMA selective genes in cMAGMA) explain a significant proportion of heritability. Top graph: Heritability enrichment ± standard error; enrichment denotes proportion of heritability/proportion of SNPs; red broken line, enrichment=1. Bottom graph: false discovery rate (FDR) of heritability enrichment: red broken line, FDR=0.05.

Extended Data Fig. 2 Heritability enrichment of brain disorders in active regulatory elements of multiple tissue/cell types.

(Top) Scaled enrichment values. (Bottom) Significance of heritability enrichment (P-values). ESC, embryonic stem cells. ESDR, embryonic stem cell derived cell lines.

Extended Data Fig. 3 Developmental expression trajectories of brain disorder risk genes derived from cMAGMA.

PCW, post-conception week; M, month; Y, year. (Left) N = 410 and 453 for prenatal and postnatal samples, respectively. Center, median; box=Q1-Q3; lower whisker, Q1 - 1.5 x IQR; upper whisker, Q3 + 1.5 x IQR. (Right) LOESS smooth curve with 95% confidence bands.

Extended Data Fig. 4 Cellular expression profiles of brain disorder risk genes.

a, Cellular expression profiles of brain disorder risk genes derived from H-MAGMA and cMAGMA. Psychiatric disorder-associated genes are highly expressed in neurons, while neurogenerative-disorder-associated genes show glial signatures. Astro, astrocytes; Micro, microglia; Endo, endothelial cells; Oligo, oligodendrocytes; OPC, oligodendrocytes progenitor cells. b, Psychiatric disorder-associated genes are highly expressed in radial glia and excitatory neurons in the developing cortex as well as excitatory neurons in the adult cortex. RG, radial glia, vRG; ventricular RG; oRG, outer RG; tRG, truncated RG; IPC, intermediate progenitor cells; Ex, excitatory neurons; In, inhibitory neurons; nEx/nIn, newly born excitatory/inhibitor neurons; PFC, prefrontal cortex; V1, visual cortex; CGE, caudal ganglionic eminence; MGE, medial ganglionic eminence.

Extended Data Fig. 5 Overlap between brain disorder risk genes derived from neuronal and astrocytic H-MAGMA.

Brain disorder risk genes (FDR<0.05) were compared between neuronal and astrocytic H-MAGMA results.

Extended Data Fig. 6 Psychiatric disorder risk genes predicted by H-MAGMA are dysregulated in postmortem brains of individuals with psychiatric disorders.

a, Overlap between common variation associated genes and genes differentially expressed (DEG) in postmortem brains with psychiatric disorders. b, Overlap between common variation associated genes and co-expression (co-exp) modules differentially regulated in psychiatric disorders. Down, modules are downregulated in disorders; Up, modules are upregulated in disorders.

Extended Data Fig. 7 Genetic relationships among brain disorders.

a, Psychiatric disorders show strong genetic relationships both at the level of genetic correlations (bottom left, rg) and gene-level overlaps (top right, RRHO). BY FDR, P-values adjusted by the Benjamini and Yekutieli procedure. b, Genetic correlations measured via LDSC (rg) are highly correlated with gene-level overlaps (RRHO Z), indicating that gene-level overlaps obtained by H-MAGMA recapitulate genetic relationships across brain disorders. Brain disorders that show strong genetic correlations (rg > 0.2) and gene-level overlaps (RRHO Z > 15) are marked in blue. Linear regression line with 95% confidence bands.

Supplementary information

Reporting Summary

Supplementary Data 1

Comparison of brain disorder risk genes identified by H-MAGMA and cMAGMA.

Supplementary Data 2

Brain disorder risk genes identified by H-MAGMA.

Supplementary Data 3

Statistical comparison between prenatal and postnatal expression values of brain disorder risk genes.

Supplementary Data 4

Gene ontologies of brain disorder risk genes based on fetal and adult brain H-MAGMA.

Supplementary Data 5

Gene ontologies of brain disorder risk genes based on cMAGMA.

Supplementary Data 6

Gene ontologies of brain disorder risk genes based on neuronal and astrocytic H-MAGMA.

Supplementary Data 7

A list of pleiotropic genes.

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Sey, N.Y.A., Hu, B., Mah, W. et al. A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles. Nat Neurosci 23, 583–593 (2020). https://doi.org/10.1038/s41593-020-0603-0

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