Biomarker and genomic analyses reveal molecular signatures of non-cardioembolic ischemic stroke

被引:8
作者
Ding, Lingling [1 ,2 ,3 ]
Liu, Yu [2 ]
Meng, Xia [2 ]
Jiang, Yong [2 ,3 ]
Lin, Jinxi [2 ]
Cheng, Si [2 ]
Xu, Zhe [2 ]
Zhao, Xingquan [1 ,2 ,3 ]
Li, Hao [2 ]
Wang, Yongjun [1 ,2 ,3 ,4 ,5 ,6 ]
Li, Zixiao [1 ,2 ,3 ,7 ,8 ]
机构
[1] Capital Med Univ, Beijing Tiantan Hosp, Dept Neurol, Beijing 100070, Peoples R China
[2] China Natl Clin Res Ctr Neurol Dis, Beijing 100070, Peoples R China
[3] Chinese Acad Med Sci, Res Unit Artificial Intelligence Cerebrovasc Dis, Beijing 100070, Peoples R China
[4] Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai 200031, Peoples R China
[5] Capital Med Univ, Adv Innovat Ctr Human Brain Protect, Beijing 100070, Peoples R China
[6] Capital Med Univ, Clin Ctr Precis Med Stroke, Beijing 100070, Peoples R China
[7] Chinese Inst Brain Res, Beijing, Peoples R China
[8] Beijing Engn Res Ctr Digital Healthcare Neurol Dis, Beijing 100070, Peoples R China
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
HOMOCYSTEINE METABOLISM; CARDIOVASCULAR-DISEASE; ATTACK DESIGN; RISK; HERITABILITY; METAANALYSIS; POPULATION; FLAVONOIDS; RECEPTOR; TRAITS;
D O I
10.1038/s41392-023-01465-w
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Acute ischemic stroke (AIS) is a major cause of disability and mortality worldwide. Non-cardioembolic ischemic stroke (NCIS), which constitutes the majority of AIS cases, is highly heterogeneous, thus requiring precision medicine treatments. This study aimed to investigate the molecular mechanisms underlying NCIS heterogeneity. We integrated data from the Third China National Stroke Registry, including clinical phenotypes, biomarkers, and whole-genome sequencing data for 7695 patients with NCIS. We identified 30 molecular clusters based on 63 biomarkers and explored the comprehensive landscape of biological heterogeneity and subpopulations in NCIS. Dimensionality reduction revealed fine-scale subpopulation structures associated with specific biomarkers. The subpopulations with biomarkers for inflammation, abnormal liver and kidney function, homocysteine metabolism, lipid metabolism, and gut microbiota metabolism were associated with a high risk of unfavorable clinical outcomes, including stroke recurrence, disability, and mortality. Several genes encoding potential drug targets were identified as putative causal genes that drive the clusters, such as CDK10, ERCC3, and CHEK2. We comprehensively characterized the genetic architecture of these subpopulations, identified their molecular signatures, and revealed the potential of the polybiomarkers and polygenic prediction for assessing clinical outcomes. Our study demonstrates the power of large-scale molecular biomarkers and genomics to understand the underlying biological mechanisms of and advance precision medicine for NCIS.
引用
收藏
页数:16
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