Evidence map›Paper›PMID 39669498›Full record

ArticleFrontiers in endocrinology2024

Elucidating the causal links between plasma and cerebrospinal fluid metabolites and pituitary tumors: a Mendelian randomization analysis.

Wencai Wang, Menghao Liu, Zun Wang, Wei Ye, Xianfeng Li

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Wencai WangDepartment of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Menghao LiuDepartment of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Zun WangDepartment of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Wei YeDepartment of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Xianfeng LiDepartment of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Pituitary tumors (PTs) are common benign intracranial tumors. Investigating the metabolites in serum and cerebrospinal fluid in PTs is essential to understanding the underlying biological mechanisms and identifying new biomarkers and therapeutic strategies. Methods: We used the GWAS dataset of PTs from the FinnGen database, a dataset of 486 plasma metabolites from the GWAS catalog database, and a dataset of 338 cerebrospinal fluid (CSF) metabolites from the WADRC and WRAP study collections. An inverse variance weighting (IVW) approach was utilized as the mainly method to investigate causality between metabolites and PTs, supplemented by four complementary methods to strengthen our findings. Additionally, we utilized several sensitivity methods to guarantee the robustness of our findings. Results: The study identified 17 plasma metabolites and 10 CSF metabolites related to PTs. Among these, 11 metabolites indicated a significant positive causality with PTs, while 16 displayed a remarkable negative causality. Particularly, plasma levels of 3-dehydrocarnitine (OR = 2.73, 95% CI = 1.55-4.83, P = 0.001) and acetylcarnitine (OR = 0.35, 95% CI = 0.19-0.63, P = 0.001) were found to be significant exposure factors for PTs. Multiple sensitivity analyses confirm the robustness of the results. The study found no evidence of a reverse causality between PTs and the plasma levels of 3-dehydrocarnitine and acetylcarnitine. Conclusions: The present study identified 27 metabolites associated with the incidence of PTs, among which 3-dehydrocarnitine and acetylcarnitine are the most noteworthy.

Indexed as

Genome-Wide Association StudyMendelian Randomization AnalysisPituitary NeoplasmsBiomarkers, TumorCarnitineFemaleHumansMaleBiomarkers, TumorCarnitine3-dehydrocarnitineacetylcarnitineMendelian randomizationmetabolitespathogenesispituitary tumors

Identifiers

PMID39669498
PMCPMC11634583

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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.