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Crowley, C. A.

Publications and source records attributed to Crowley, C. A..

2 recordsLinked to original sources

VAMPIRE: A model blood cell trait focused annotation tool for interpretation and prioritization of complex trait genome-wide association study results

Genome-wide association studies (GWAS) have identified hundreds of thousands of genetic variants associated with complex diseases and traits. However, most variants are noncoding and not clearly linked to genes, making it challenging to interpret these GWAS signals. We present a systematic variant-to-function study, prioritizing the most likely functional elements of the genome for experimental follow-up, for >148,000 variants identified for hematological traits. Specifically, we developed VAMPIRE: Variant Annotation Method Pointing to Interesting Regulatory Effects, an interactive web application implemented in R Shiny (http://shiny.bios.unc.edu/vampire/). This tool efficiently integrates and displays information from multiple complementary sources, including epigenomic signatures from blood cell relevant tissues or cells, functional and conservation summary scores, variant impact on protein and gene expression, chromatin conformation information, as well as publicly available GWAS and phenome-wide association study (PheWAS) results. Leveraging data generated from independently performed functional validation experiments, we demonstrate that our prioritized variants, genes, or variant-gene links are significantly more likely to be experimentally validated. This study not only has important implications for systematic and efficient revelation of functional mechanisms underlying GWAS variants for hematological traits, but also provides a prototype that can be adapted to many other complex traits, paving the path for efficient variant to function (V2F) analyses.

genetics

Neuronal and glial 3D chromatin architecture illustrates cellular etiology of brain disorders

Cellular heterogeneity in the human brain obscures the identification of robust cellular regulatory networks. Here we integrated genome-wide chromosome conformation in purified neurons and glia with transcriptomic and enhancer profiles to build the gene regulatory landscape of two major cell classes in the human brain. Within glutamatergic and GABAergic neurons, we were able to link enhancers to their cognate genes via neuronal chromatin interaction profiles. These cell-type-specific regulatory landscapes were then leveraged to gain insight into the cellular etiology of several brain disorders. We found that Alzheimers disease (AD)-associated epigenetic dysregulation was linked to neurons and oligodendrocytes, whereas genetic risk factors for AD highlighted microglia as a central cell type, suggesting that different cell types may confer risk to the disease via different genetic mechanisms. Moreover, neuronal subtype-specific annotation of genetic risk factors for schizophrenia and bipolar disorder identified shared (parvalbumin-expressing interneurons) and distinct cellular etiology (upper layer neurons for bipolar and deeper layer projection neurons for schizophrenia) between these two closely related psychiatric illnesses. Collectively, these findings shed new light on cell-type-specific gene regulatory networks in brain disorders.

neuroscience