Evidence map›Paper›PMID 39348397›Full record

ArticlePloS one2024

Mendelian randomization analysis reveals causal association of anthropometric measures on sepsis risk and mortality.

Chu-Yun Liu, Yu-Shen Yang, Meng-Qin Pei, He-Fan He

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Chu-Yun LiuDepartment of Anesthesiology, the Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China.
Yu-Shen YangDepartment of Anesthesiology, the Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China.
Meng-Qin PeiDepartment of Anesthesiology, the Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China.
He-Fan HeDepartment of Anesthesiology, the Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China.ORCID 0000-0003-0310-3999

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The objective of this study was to explore the potential causalities of fat mass, nonfat mass and height (henceforth, 'anthropometric measures') with sepsis risk and mortality. We conducted the Mendelian randomization (MR) investigation using genome-wide association study (GWAS) summary statistics of anthropometric measures, sepsis, and sepsis mortality. The GWAS summary data from the UK Biobank was used. Firstly, MR analysis was performed to estimate the causal effect of anthropometric measures on the risk of sepsis. The inverse-variance weighted (IVW) method was utilized as the primary analytical approach, together with weighted median-based method. Cochrane's Q test and MR-Egger intercept test were performed to assess heterogeneity and pleiotropy, respectively. Finally, we performed a series of sensitivity analyses to enhance the precision and veracity of our findings. The IVW method showed that genetically predicted weight-related measures were suggestively linked to an increased risk of sepsis. However, height displayed no causal association with sepsis risk and mortality. Furthermore, weight-related measures also displayed significant MR association with the sepsis mortality, except body nonfat mass and right leg nonfat mass. However, MVMR analysis indicated the observed effects for weight-related measures in the univariable MR analyses are more likely a bias caused by the interrelationship between anthropometric measures. According to the MR-Egger intercept assessment, our MR examination was not influenced by horizontal pleiotropy (all p>0.05). Moreover, the reliability of the estimated causal association was confirmed by the sensitivity analyses. In conclusion, these findings provided vital new knowledge on the role of anthropometric-related measures in the sepsis etiology.

Indexed as

Genome-Wide Association StudyMendelian Randomization AnalysisSepsisAnthropometryBody HeightFemaleHumansMalePolymorphism, Single NucleotideRisk Factors

Identifiers

PMID39348397
PMCPMC11441680

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