2022
DOI: 10.1186/s12916-022-02408-y
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Identification of novel proteins for lacunar stroke by integrating genome-wide association data and human brain proteomes

Abstract: Background Previous genome-wide association studies (GWAS) have identified numerous risk genes for lacunar stroke, but it is challenging to decipher how they confer risk for the disease. We employed an integrative analytical pipeline to efficiently transform genetic associations to identify novel proteins for lacunar stroke. Methods We systematically integrated lacunar stroke genome-wide association study (GWAS) (N=7338) with human brain proteomes … Show more

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Cited by 28 publications
(18 citation statements)
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“…This is as a highly plausible prioritized gene that is likely to modulate the metabolism of amyloid precursor protein (APP) (23) and increase risk of AD. ICA1L encodes a protein whose expression is activated by type IV collagen and plays a crucial role in myelination (46). Increased ICA1L expression is also associated with lower risk of AD (47)(48)(49) and small vessel strokes (SVS), the acute outcomes of cerebral SVD, which may lead to VaD (50).…”
Section: Discussionmentioning
confidence: 99%
“…This is as a highly plausible prioritized gene that is likely to modulate the metabolism of amyloid precursor protein (APP) (23) and increase risk of AD. ICA1L encodes a protein whose expression is activated by type IV collagen and plays a crucial role in myelination (46). Increased ICA1L expression is also associated with lower risk of AD (47)(48)(49) and small vessel strokes (SVS), the acute outcomes of cerebral SVD, which may lead to VaD (50).…”
Section: Discussionmentioning
confidence: 99%
“…Cis‐regulated brain protein levels of the PTPN11 gene are associated with lacunar stroke, and this gene is expressed on the surface of glutaminergic neurons, aminobutyric acid neurons, and astrocytes (Zhang et al, 2022). Lacunar cerebral infarction is mainly caused by AS and the occlusion of small perforated arteries caused by long‐term hypertension, diabetes, and other risk factors.…”
Section: Discussionmentioning
confidence: 99%
“…Subsequently, the genetic impact of CHD and MI (GWAS Z scores for CHD and MI) was combined with mRNA expression weights. Using the FUSION platform, we calculated the TWAS expression weights (i.e., SNP-gene expression correlations) based on the reference transcriptome [ 27 ]. In our analysis, we employed several prediction models, including top1, blup, lasso, enet, and bslmm.…”
Section: Methodsmentioning
confidence: 99%