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DOI 10.1016/j.jstrokecerebrovasdis.2025.108285

Медицинская библиотека · Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association · 2025

Multiomics analysis demonstrated a strong correlation between lipid-mediated chronic kidney disease and stroke: Potential benefits of affected patient cohorts.

Liu Yan-Song, Zhang Jian-Hang, Han Jia-Yue, Long Yu-Yan, Liu Yu-Chen, Mao Kai-Ni, Feng Yu-Jing, Song Zhi-Guang, Peng Si-Min, Tan Shi-Min, Cai Si-le, Yang Jing-Yi, Lin Li-Hua, Song Wan-Ying, Li Hua, Liu Wang-Hua

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Аннотация

OBJECTIVE

Patients with chronic kidney disease (CKD) exhibit a disproportionately elevated risk of stroke, frequently compounded by renal impairment. Therapeutic strategies for stroke based on Traditional Chinese Medicine's 'kidney-brain axis' theory demonstrate clinical efficacy, indicating that there may be a potential association between chronic kidney disease and stroke, which needs further exploration and verification.

METHODS

In this study, databases such as GEO, NHANES, and GWAS were used to collect data related to CKD and stroke. GEO gene data enrichment analysis was used to explore possible mediating factors between CKD and stroke. NHANES clinical data were used to verify the GEO data analysis results. Mendelian randomization was used to confirm the causal relationship between CKD and stroke and verify the association effect of mediating factors in these two diseases.

RESULTS

Cross-gene analysis and transcription factor analysis of GEO data revealed that lipid-related pathways may have a mediating effect on the relationship between CKD and stroke. Logistic regression analysis based on NHANES data revealed that changes in LDL-C, HDL-C, TC, and TG can affect the occurrence of stroke. Mendelian randomization analysis was used to determine the causal relationship between CKD and stroke and verified the mediating effects of lipid factors, such as LDL-C, HDL-C, TC, and TG, indicating that LDL-C, HDL-C, TC, and TG may be potential mediating factors for these two diseases. Our findings highlight the clinical relevance of lipid pathways in bridging CKD and stroke. By integrating predictive biomarkers and multi-level diagnostics, this study paves the way for AI-driven precision medicine in stroke prevention. Specifically, machine learning approaches could enhance risk stratification of high-risk CKD cohorts, enabling tailored interventions such as lipid-lowering therapies and personalized monitoring protocols. These strategies align with emerging paradigms in healthcare benefits and population-specific management.

CONCLUSION

This study provides new insights into the interactive relationship between CKD and stroke and provides a scientific basis for the process of syndrome differentiation and the treatment of stroke under the guidance of the "kidney-brain correlation". Moreover, the influence of mediating factors related to lipid metabolism on the occurrence of these two diseases was investigated, which deepened researchers' understanding of the potential association mechanism between the two diseases.

Для цитирования: Liu Yan-Song, Zhang Jian-Hang, Han Jia-Yue, Long Yu-Yan, Liu Yu-Chen, Mao Kai-Ni, Feng Yu-Jing, Song Zhi-Guang, Peng Si-Min, Tan Shi-Min, Cai Si-le, Yang Jing-Yi, Lin Li-Hua, Song Wan-Ying, Li Hua, Liu Wang-Hua. Multiomics analysis demonstrated a strong correlation between lipid-mediated chronic kidney disease and stroke: Potential benefits of affected patient cohorts.. Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association. 2025. DOI: 10.1016/j.jstrokecerebrovasdis.2025.108285.

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