CSEA-DB: an omnibus for human complex trait and cell type associations

Dai, Yulin; Hu, Ruifeng; Manuel, Astrid M.; Liu, Andi; Jia, Peilin; Zhao, Zhongming

doi:10.1093/nar/gkaa1064

Cited by 23 publications

(30 citation statements)

References 33 publications

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“…According to our tissue cell-type-specific expression database (CSEA-DB), CXCR6 is mainly expressed in immune cells in human lung tissue (e.g., T cell and NK cell) [16]. In Liao et al’s work, the authors reported that CXCR6 had lower expression in severe patients than moderate patients, indicating a potential protective effect in T cells of human respiratory systems [17].…”

Section: Resultsmentioning

confidence: 99%

“…Recent advances in single cell transcriptome sequencing provide unprecedented opportunities to understand the biological mechanism underlying disease pathogenesis at the single cell and cell type levels [14][15][16]. The recent generation of single cell RNA-sequencing (scRNA-seq) data from the bronchoalveolar lavage fluid (BALF) of moderate and severe COVID-19 patients has revealed the landscape of the gene expression changes in major immune cells.…”

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confidence: 99%

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Association ofCXCR6with COVID-19 severity: Delineating the host genetic factors in transcriptomic regulation

Dai

Wang

Jeong

et al. 2021

Preprint

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Background: The coronavirus disease 2019 (COVID-19) is an infectious disease that mainly affects the host respiratory system with ~80% asymptomatic or mild cases and ~5% severe cases. Recent genome-wide association studies (GWAS) have identified several genetic loci associated with the severe COVID-19 symptoms. Delineating the genetic variants and genes is important for better understanding its biological mechanisms. Methods: We implemented integrative approaches, including transcriptome-wide association studies (TWAS) and colocalization analysis, to interpret the genetic risks using two independent GWAS datasets in lung and immune cells. We further performed single cell transcriptomic analysis on a bronchoalveolar lavage fluid (BALF) dataset from moderate and severe COVID-19 patients. Results: We discovered and replicated the genetically regulated expression of CXCR6 and CCR9 genes. These two genes have a protective effect on the lung and a risk effect on whole blood, respectively. The colocalization analysis of GWAS and cis-expression quantitative trait loci highlighted the regulatory effect on CXCR6 expression in lung and immune cells. In the lung resident memory CD8+ T (TRM) cells, we found a 3.32-fold decrease of cell proportion and lower expression of CXCR6 in the severe than moderate patients using the BALF transcriptomic dataset. Conclusion: CXCR6 from the 3p21.31 locus is associated with severe COVID-19. CXCR6 tends to have a lower expression in lung TRM cells of severe patients, which aligns with the protective effect of CXCR6 from TWAS analysis. We illustrate one potential mechanism of host genetic factor impacting the severity of COVID-19 through regulating the expression of CXCR6 and TRM cell proportion. Our results shed light on potential therapeutic targets for severe COVID-19.

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Section: Resultsmentioning

confidence: 99%

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confidence: 99%

Association ofCXCR6with COVID-19 severity: Delineating the host genetic factors in transcriptomic regulation

Dai

Wang

Jeong

et al. 2021

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“…In recent years, large consortia like GTEx (Genotype-Tissue Expression), eQTLGen Consortium, and DICE (database of immune cell expression) have generated rich eQTLs resources in diverse tissues and immune-related cell types (GTEx Consortium 2020 ; Schmiedel et al 2018 ; Võsa et al 2018a ). A variety of statistical approaches, such as transcriptome-wide association study (TWAS) analysis and colocalization analysis, have successfully interpreted the target genes of non-coding variants by integrating the context-specific eQTLs (Dai et al 2020 ; Dai et al 2019 ; Gamazon et al 2015; Giambartolomei et al 2014 ).…”

Section: Introductionmentioning

confidence: 99%

Association of CXCR6 with COVID-19 severity: delineating the host genetic factors in transcriptomic regulation

et al. 2021

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The coronavirus disease 2019 (COVID-19) is an infectious disease that mainly affects the host respiratory system with ~ 80% asymptomatic or mild cases and ~ 5% severe cases. Recent genome-wide association studies (GWAS) have identified several genetic loci associated with the severe COVID-19 symptoms. Delineating the genetic variants and genes is important for better understanding its biological mechanisms. We implemented integrative approaches, including transcriptome-wide association studies (TWAS), colocalization analysis, and functional element prediction analysis, to interpret the genetic risks using two independent GWAS datasets in lung and immune cells. To understand the context-specific molecular alteration, we further performed deep learning-based single-cell transcriptomic analyses on a bronchoalveolar lavage fluid (BALF) dataset from moderate and severe COVID-19 patients. We discovered and replicated the genetically regulated expression of CXCR6 and CCR9 genes. These two genes have a protective effect on lung, and a risk effect on whole blood, respectively. The colocalization analysis of GWAS and cis -expression quantitative trait loci highlighted the regulatory effect on CXCR6 expression in lung and immune cells. In the lung-resident memory CD8 + T (T RM ) cells, we found a 2.24-fold decrease of cell proportion among CD8 + T cells and lower expression of CXCR6 in the severe patients than moderate patients. Pro-inflammatory transcriptional programs were highlighted in the T RM cellular trajectory from moderate to severe patients. CXCR6 from the 3p21.31 locus is associated with severe COVID-19. CXCR6 tends to have a lower expression in lung T RM cells of severe patients, which aligns with the protective effect of CXCR6 from TWAS analysis. Supplementary Information The online version contains supplementary material available at 10.1007/s00439-021-02305-z.

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“…We applied deCS algorithm to the GWAS data in our recently developed database, Cell type-Specific Enrichment Analysis DataBase (CSEA-DB), which covers 55 unique tissues [69]. Among a total of 10,250,480 trait-cell type associations, we observed significant cell type association in 598 (11.68%) traits.…”

Section: Discussionmentioning

confidence: 99%

deCS: A Tool for Systematic Cell Type Annotations of Single-cell RNA Sequencing Data among Human Tissues

Pei

Yan

Simon

et al. 2021

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Single-cell RNA sequencing (scRNA-seq) is revolutionizing the study of complex and dynamic cellular mechanisms. However, cell-type annotation remains a main challenge as it largely relies on manual curation, which is cumbersome and less accurate. The increasing number of scRNA-seq data sets, as well as numerous published genetic studies, motivated us to build a comprehensive human cell type reference atlas. Here, we present deCS (decoding Cell type-Specificity), an automatic cell type annotation method based on a comprehensive collection of human cell type expression profiles or a list of marker genes. We applied deCS to single-cell data sets from various tissue types, and systematically evaluated the annotation accuracy under various conditions, including reference panels, sequencing depth and feature selection. Our results demonstrated that expanding the references is critical for improving annotation accuracy. Compared to the existing state-of-the-art annotation tools, deCS significantly reduced computation time while increased accuracy. deCS can be integrated into the standard scRNA-seq analytical pipeline to enhance cell type annotation. Finally, we demonstrated the broad utility of deCS to identify trait-cell type associations in 51 human complex traits, providing deeper insight into the cellular mechanisms of disease pathogenesis.

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CSEA-DB: an omnibus for human complex trait and cell type associations

Cited by 23 publications

References 33 publications

Association ofCXCR6with COVID-19 severity: Delineating the host genetic factors in transcriptomic regulation

Association ofCXCR6with COVID-19 severity: Delineating the host genetic factors in transcriptomic regulation

Association of CXCR6 with COVID-19 severity: delineating the host genetic factors in transcriptomic regulation

deCS: A Tool for Systematic Cell Type Annotations of Single-cell RNA Sequencing Data among Human Tissues

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