Evidence map›Paper›PMID 37805474›Full record

SynthesisBMC infectious diseases2023

Causal relationship between blood metabolites and risk of five infections: a Mendelian randomization study.

Zhengxiao Wei, Qingqing Xiong, Dan Huang, Zhangjun Wu, Zhu Chen

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in BMC infectious diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.1field-weighted citation impact, top 22% of its field
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

7 citing papers in PubMed, 7 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Zhengxiao Wei *Department of Clinical Laboratory, Chengdu Public Health Clinical Medical Center & Public Health Clinical Center of Chengdu University of Traditional Chinese Medicine, 377 Jingming Road, Jinjiang District, Chengdu, 610066, China. weizhengxiao@outlook.com.ORCID http://orcid.org/0000-0001-5065-7623
Qingqing Xiong *Department of Scientific Research and Teaching, Chengdu Public Health Clinical Medical Center & Public Health Clinical Center of Chengdu University of Traditional Chinese Medicine, 377 Jingming Road, Jinjiang District, Chengdu, 610066, China.
Dan HuangDepartment of Clinical Laboratory, Chengdu Public Health Clinical Medical Center & Public Health Clinical Center of Chengdu University of Traditional Chinese Medicine, 377 Jingming Road, Jinjiang District, Chengdu, 610066, China.
Zhangjun WuDepartment of Clinical Laboratory, Chengdu Public Health Clinical Medical Center & Public Health Clinical Center of Chengdu University of Traditional Chinese Medicine, 377 Jingming Road, Jinjiang District, Chengdu, 610066, China.
Zhu ChenDepartment of Scientific Research and Teaching, Chengdu Public Health Clinical Medical Center & Public Health Clinical Center of Chengdu University of Traditional Chinese Medicine, 377 Jingming Road, Jinjiang District, Chengdu, 610066, China.
Public Health Clinical Center of Chengdu · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveInfectious diseases continue to pose a significant threat in the field of global public health, and our understanding of their metabolic pathogenesis remains limited. However, the advent of genome-wide association studies (GWAS) offers an unprecedented opportunity to unravel the relationship between metabolites and infections.

methodsUnivariable and multivariable Mendelian randomization (MR) was commandeered to elucidate the causal relationship between blood metabolism and five high-frequency infection phenotypes: sepsis, pneumonia, upper respiratory tract infections (URTI), urinary tract infections (UTI), and skin and subcutaneous tissue infection (SSTI). GWAS data for infections were derived from UK Biobank and the FinnGen consortium. The primary analysis was conducted using the inverse variance weighted method on the UK Biobank data, along with a series of sensitivity analyses. Subsequently, replication and meta-analysis were performed on the FinnGen consortium data.

resultsAfter primary analysis and a series of sensitivity analyses, 17 metabolites were identified from UK Biobank that have a causal relationship with five infections. Upon joint analysis with the FinGen cohort, 7 of these metabolites demonstrated consistent associations. Subsequently, we conducted a multivariable Mendelian randomization analysis to confirm the independent effects of these metabolites. Among known metabolites, genetically predicted 1-stearoylglycerol (1-SG) (odds ratio [OR] = 0.561, 95% confidence interval [CI]: 0.403-0.780, P < 0.001) and 3-carboxy-4-methyl-5-propyl-2-furanpropanoate (CMPF) (OR = 0.780, 95%CI: 0.689-0.883, P < 0.001) was causatively associated with a lower risk of sepsis, and genetically predicted phenylacetate (PA) (OR = 1.426, 95%CI: 1.152-1.765, P = 0.001) and cysteine (OR = 1.522, 95%CI: 1.170-1.980, P = 0.002) were associated with an increased risk of UTI. Ursodeoxycholate (UDCA) (OR = 0.906, 95%CI: 0.829-0.990, P = 0.029) is a protective factor against pneumonia. Two unknown metabolites, X-12407 (OR = 1.294, 95%CI: 1.131-1.481, P < 0.001), and X-12847 (OR = 1.344, 95%CI: 1.152-1.568, P < 0.001), were also identified as independent risk factors for sepsis.

conclusionsIn this MR study, we demonstrated a causal relationship between blood metabolites and the risk of developing sepsis, pneumonia, and UTI. However, there was no evidence of a causal connection between blood metabolites and the risk of URTI or SSTI, indicating a need for larger-scale studies to further investigate susceptibility to certain infection phenotypes.

Indexed as

Nose DiseasesPneumoniaRespiratory Tract InfectionsSepsisCausalityGenome-Wide Association StudyHumansMendelian Randomization AnalysisPolymorphism, Single NucleotideBlood metabolitesInfectionsMendelian randomizationPneumoniaSepsisUrinary tract infection

Identifiers

PMID37805474
PMCPMC10559484
OpenAlexW4387428797

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.