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1.
Bioinformatics ; 39(1)2023 01 01.
Article in English | MEDLINE | ID: mdl-36495218

ABSTRACT

SUMMARY: With the continued deluge of results from genome-wide association and functional genomic studies, it has become increasingly imperative to quickly combine and visualize different layers of genetic and genomic data within a given locus to facilitate exploratory and integrative data analyses. While several tools have been developed to visualize locus-level genetic results, the limited speed, scalability and flexibility of current approaches remain a significant bottleneck. Here, we present a Julia package for high-performance genetics and genomics-related data visualization that enables fast, simultaneous plotting of hundreds of association results along with multiple relevant genomic annotations. Leveraging the powerful plotting and layout utilities from Makie.jl facilitates the customization and extensibility of every component of a plot, enabling generation of publication-ready figures. AVAILABILITY AND IMPLEMENTATION: The GeneticsMakie.jl package is open source and distributed under the MIT license via GitHub (https://github.com/mmkim1210/GeneticsMakie.jl). The GitHub repository contains installation instructions as well as examples and documentation for built-in functions. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.


Subject(s)
Genome-Wide Association Study , Software , Genome-Wide Association Study/methods , Genomics/methods , Genome , Data Analysis
2.
Sci Adv ; 10(21): eadn7655, 2024 May 24.
Article in English | MEDLINE | ID: mdl-38781333

ABSTRACT

Few neuropsychiatric disorders have replicable biomarkers, prompting high-resolution and large-scale molecular studies. However, we still lack consensus on a more foundational question: whether quantitative shifts in cell types-the functional unit of life-contribute to neuropsychiatric disorders. Leveraging advances in human brain single-cell methylomics, we deconvolve seven major cell types using bulk DNA methylation profiling across 1270 postmortem brains, including from individuals diagnosed with Alzheimer's disease, schizophrenia, and autism. We observe and replicate cell-type compositional shifts for Alzheimer's disease (endothelial cell loss), autism (increased microglia), and schizophrenia (decreased oligodendrocytes), and find age- and sex-related changes. Multiple layers of evidence indicate that endothelial cell loss contributes to Alzheimer's disease, with comparable effect size to APOE genotype among older people. Genome-wide association identified five genetic loci related to cell-type composition, involving plausible genes for the neurovascular unit (P2RX5 and TRPV3) and excitatory neurons (DPY30 and MEMO1). These results implicate specific cell-type shifts in the pathophysiology of neuropsychiatric disorders.


Subject(s)
Alzheimer Disease , Autistic Disorder , Brain , DNA Methylation , Schizophrenia , Humans , Alzheimer Disease/genetics , Alzheimer Disease/pathology , Alzheimer Disease/metabolism , Schizophrenia/genetics , Schizophrenia/pathology , Brain/metabolism , Brain/pathology , Autistic Disorder/genetics , Autistic Disorder/pathology , Male , Female , Genome-Wide Association Study , Aged , Endothelial Cells/metabolism , Endothelial Cells/pathology , Epigenomics/methods , Middle Aged , Aged, 80 and over
3.
Science ; 384(6698): eadh0829, 2024 May 24.
Article in English | MEDLINE | ID: mdl-38781368

ABSTRACT

Neuropsychiatric genome-wide association studies (GWASs), including those for autism spectrum disorder and schizophrenia, show strong enrichment for regulatory elements in the developing brain. However, prioritizing risk genes and mechanisms is challenging without a unified regulatory atlas. Across 672 diverse developing human brains, we identified 15,752 genes harboring gene, isoform, and/or splicing quantitative trait loci, mapping 3739 to cellular contexts. Gene expression heritability drops during development, likely reflecting both increasing cellular heterogeneity and the intrinsic properties of neuronal maturation. Isoform-level regulation, particularly in the second trimester, mediated the largest proportion of GWAS heritability. Through colocalization, we prioritized mechanisms for about 60% of GWAS loci across five disorders, exceeding adult brain findings. Finally, we contextualized results within gene and isoform coexpression networks, revealing the comprehensive landscape of transcriptome regulation in development and disease.


Subject(s)
Alternative Splicing , Brain , Gene Expression Regulation, Developmental , Mental Disorders , Humans , Atlases as Topic , Autism Spectrum Disorder/genetics , Brain/metabolism , Brain/growth & development , Brain/embryology , Gene Regulatory Networks , Genome-Wide Association Study , Protein Isoforms/genetics , Protein Isoforms/metabolism , Quantitative Trait Loci , Schizophrenia/genetics , Transcriptome , Mental Disorders/genetics
4.
Nat Genet ; 55(12): 2117-2128, 2023 Dec.
Article in English | MEDLINE | ID: mdl-38036788

ABSTRACT

Methods integrating genetics with transcriptomic reference panels prioritize risk genes and mechanisms at only a fraction of trait-associated genetic loci, due in part to an overreliance on total gene expression as a molecular outcome measure. This challenge is particularly relevant for the brain, in which extensive splicing generates multiple distinct transcript-isoforms per gene. Due to complex correlation structures, isoform-level modeling from cis-window variants requires methodological innovation. Here we introduce isoTWAS, a multivariate, stepwise framework integrating genetics, isoform-level expression and phenotypic associations. Compared to gene-level methods, isoTWAS improves both isoform and gene expression prediction, yielding more testable genes, and increased power for discovery of trait associations within genome-wide association study loci across 15 neuropsychiatric traits. We illustrate multiple isoTWAS associations undetectable at the gene-level, prioritizing isoforms of AKT3, CUL3 and HSPD1 in schizophrenia and PCLO with multiple disorders. Results highlight the importance of incorporating isoform-level resolution within integrative approaches to increase discovery of trait associations, especially for brain-relevant traits.


Subject(s)
Genome-Wide Association Study , Transcriptome , Humans , Transcriptome/genetics , Genome-Wide Association Study/methods , Quantitative Trait Loci/genetics , Genetic Predisposition to Disease , Brain/metabolism , Protein Isoforms/metabolism , Polymorphism, Single Nucleotide
5.
medRxiv ; 2023 Mar 06.
Article in English | MEDLINE | ID: mdl-36945630

ABSTRACT

Genomic regulatory elements active in the developing human brain are notably enriched in genetic risk for neuropsychiatric disorders, including autism spectrum disorder (ASD), schizophrenia, and bipolar disorder. However, prioritizing the specific risk genes and candidate molecular mechanisms underlying these genetic enrichments has been hindered by the lack of a single unified large-scale gene regulatory atlas of human brain development. Here, we uniformly process and systematically characterize gene, isoform, and splicing quantitative trait loci (xQTLs) in 672 fetal brain samples from unique subjects across multiple ancestral populations. We identify 15,752 genes harboring a significant xQTL and map 3,739 eQTLs to a specific cellular context. We observe a striking drop in gene expression and splicing heritability as the human brain develops. Isoform-level regulation, particularly in the second trimester, mediates the greatest proportion of heritability across multiple psychiatric GWAS, compared with eQTLs. Via colocalization and TWAS, we prioritize biological mechanisms for ~60% of GWAS loci across five neuropsychiatric disorders, nearly two-fold that observed in the adult brain. Finally, we build a comprehensive set of developmentally regulated gene and isoform co-expression networks capturing unique genetic enrichments across disorders. Together, this work provides a comprehensive view of genetic regulation across human brain development as well as the stage-and cell type-informed mechanistic underpinnings of neuropsychiatric disorders.

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