Evidence map›Paper›PMID 40612664›Full record

ArticleGenes & diseases2025

Genetically predicted blood metabolites mediate the association between immune cell characteristics and urolithiasis: A Mendelian randomization study and mediation analysis.

Chengcheng Wei, Jiatai He, Jun Wen, Shunyao Wang, Mengjia Shi, Juan Hu, Huanhuan Tan, Jinjun Guo, Xiaosong Li

Abstract read
In one paragraph

Article in Genes & diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Virtual single-cell perturbation and genetic causal inference revealJournal of cell communication and signaling · 2026
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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Chengcheng WeiDepartment of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
Jiatai HeDepartment of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.
Jun WenDepartment of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing Medical University, Chongqing 400016, China.
Shunyao WangClinical Molecular Medicine Testing Center, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
Mengjia ShiClinical Molecular Medicine Testing Center, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
Juan HuDepartment of Clinical Laboratory Medicine Suining Central Hospital, Suining, Sichuan 629000, China.
Huanhuan TanReproductive Medicine Center, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
Jinjun GuoBishan Hospital of Chongqing, Bishan Hospital of Chongqing Medical University, Chongqing 402760, China.
Xiaosong LiClinical Molecular Medicine Testing Center, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Urolithiasis, a disease characterized by the formation of urinary stones, is influenced by immune system dysregulation and metabolic factors. This study investigated the interplay between specific immune cell characteristics and blood metabolites in urolithiasis based on Mendelian randomization. We further explored the potential mediating effects of genetically predicted blood metabolites based on mediation analysis. We employed a two-sample Mendelian randomization analysis to examine the association between immune cell properties, blood metabolites, and urolithiasis risk. Genetic instruments for immune cell characteristics and blood metabolites were used to assess causal relationships and mediating pathways. Our results indicate that 10 immune cell characteristics had a unidirectional causal association with urolithiasis risk. We also detected 13 blood metabolites associated with urolithiasis. We identified 4 pathways through which genetically predicted blood metabolites partly mediated the association between specific immune cell characteristics and urolithiasis risk. This suggests potential mechanistic links where altered blood metabolites may play a role in developing urolithiasis through immune system modulation. This Mendelian randomization study highlights the complex relationship between immune responses, blood metabolites, and urolithiasis. The findings underscore the importance of considering both immune cell features and metabolic factors in understanding the pathogenesis of urolithiasis, offering insights into novel therapeutic targets and diagnostic strategies for this disorder.

Indexed as

Blood metabolitesImmunityMediation analysisMendelian randomization studyUrolithiasis

Identifiers

PMID40612664
PMCPMC12226092

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.