Evidence map›Paper›PMID 38975226›Full record

ArticleHeliyon2024

Mendelian randomization analysis identifies causal associations between serum lipidomic profile, amino acid biomarkers and sepsis.

Zi-Gang Zhu, Jia-Wei Ma, Dan-Dan Ji, Qian-Qian Li, Xin-Yu Diao, Jie Bao

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Zi-Gang ZhuDepartment of Critical Care Medicine, Jiangnan University Medical Center,Wuxi No.2 People's Hospital, Wuxi, 214002, China.
Jia-Wei MaDepartment of Critical Care Medicine, Jiangnan University Medical Center,Wuxi No.2 People's Hospital, Wuxi, 214002, China.
Dan-Dan JiDepartment of Critical Care Medicine, Jiangnan University Medical Center,Wuxi No.2 People's Hospital, Wuxi, 214002, China.
Qian-Qian LiDepartment of Critical Care Medicine, Jiangnan University Medical Center,Wuxi No.2 People's Hospital, Wuxi, 214002, China.
Xin-Yu DiaoEmergency Department, Yixing Traditional Chinese Medicine Hospital, Yixing,214299,China.
Jie BaoDepartment of Critical Care Medicine, Jiangnan University Medical Center,Wuxi No.2 People's Hospital, Wuxi, 214002, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Sepsis is a life-threatening condition marked by a severe systemic response to infection, leading to widespread inflammation, cellular signaling disruption, and metabolic dysregulation. The role of lipid and amino acid metabolism in sepsis is not fully understood, but aberrations in this pathway could contribute to the disease's pathophysiology. Methods: To explore the potential of lipid and amino acid compounds as biomarkers for the diagnosis and prognosis of sepsis, a two-sample Mendelian Randomization (MR) study was conducted, examining the relationship between sepsis and 249 serum lipid and amino acid-related markers. Key enzymes involved in synthesis of phosphatidylcholine, including choline/ethanolamine phosphotransferase 1 (CEPT1), choline phosphotransferase 1 (CPT1), and ethanolamine phosphotransferase 1 (EPT1), were also targeted for drug-target Mendelian randomization. Results: The study found that phosphatidylcholines (OR Conclusion: Our findings suggest that increasing levels of phosphatidylcholines and medium HDL phospholipids may reduce the incidence of sepsis. This highlights the potential of lipid-based biomarkers in the diagnosis and management of sepsis, opening avenues for new therapeutic strategies.

Indexed as

Amino acidLipid metabolismMendelian randomizationPhosphatidylcholineSepsis

Identifiers

PMID38975226
PMCPMC11226841

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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.