Dataset Information

Identifying causal genes for stroke via integrating the proteome and transcriptome from brain and blood.

ABSTRACT:

Background

Genome-wide association studies (GWAS) have revealed numerous loci associated with stroke. However, the underlying mechanisms at these loci in the pathogenesis of stroke and effective stroke drug targets are elusive. Therefore, we aimed to identify causal genes in the pathogenesis of stroke and its subtypes.

Methods

Utilizing multidimensional high-throughput data generated, we integrated proteome-wide association study (PWAS), transcriptome-wide association study (TWAS), Mendelian randomization (MR), and Bayesian colocalization analysis to prioritize genes that contribute to stroke and its subtypes risk via affecting their expression and protein abundance in brain and blood.

Results

Our integrative analysis revealed that ICA1L was associated with small-vessel stroke (SVS), according to robust evidence at both protein and transcriptional levels based on brain-derived data. We also identified NBEAL1 that was causally related to SVS via its cis-regulated brain expression level. In blood, we identified 5 genes (MMP12, SCARF1, ABO, F11, and CKAP2) that had causal relationships with stroke and stroke subtypes.

Conclusions

Together, via using an integrative analysis to deal with multidimensional data, we prioritized causal genes in the pathogenesis of SVS, which offered hints for future biological and therapeutic studies.

SUBMITTER: Wu BS

PROVIDER: S-EPMC9022281 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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Publications

Identifying causal genes for stroke via integrating the proteome and transcriptome from brain and blood.

Wu Bang-Sheng BS Chen Shu-Fen SF Huang Shu-Yi SY Ou Ya-Nan YN Deng Yue-Ting YT Chen Shi-Dong SD Dong Qiang Q Yu Jin-Tai JT

Journal of translational medicine 20220421 1

<h4>Background</h4>Genome-wide association studies (GWAS) have revealed numerous loci associated with stroke. However, the underlying mechanisms at these loci in the pathogenesis of stroke and effective stroke drug targets are elusive. Therefore, we aimed to identify causal genes in the pathogenesis of stroke and its subtypes.<h4>Methods</h4>Utilizing multidimensional high-throughput data generated, we integrated proteome-wide association study (PWAS), transcriptome-wide association study (TWAS) ...[more]

PMID: 35449099

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Dataset Information

Identifying causal genes for stroke via integrating the proteome and transcriptome from brain and blood.

Background

Methods

Results

Conclusions

Publications

Identifying causal genes for stroke via integrating the proteome and transcriptome from brain and blood.

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