Evidence map›Paper›PMID 38951678›Full record

ArticleHypertension research : official journal of the Japanese Society of Hypertension2024

BMA-based Mendelian randomization identifies blood metabolites as causal candidates in pregnancy-induced hypertension.

Jun Guo, Xiaofei Zheng, Xue Du, Weisheng Li, Likui Lu

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Article in Hypertension research : official journal of the Japanese Society of Hypertension, 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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5 · Who and what money

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5 authors.

Jun Guo *Department of Obstetrics and Gynecology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230001, Anhui, China.
Xiaofei Zheng *Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Xue DuDepartment of Obstetrics and Gynecology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230001, Anhui, China.
Weisheng LiDepartment of gynaecology, Qingdao Hospital, University of Health and Rehabilitation Sciences (Qingdao Municipal Hospital), Qingdao, China. levis_119@163.com.
Likui LuDepartment of Obstetrics and Gynecology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230001, Anhui, China. lulikui0801@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pregnancy-induced hypertension (PIH), a prominent determinant of maternal mortality and morbidity worldwide, is hindered by the absence of efficacious biomarkers for early diagnosis, contributing to suboptimal outcomes. Here, we explored potential causal relationships between blood metabolites and the risk of PIH using Mendelian randomization (MR). We employed a two-sample univariable MR approach to empirically estimate the causal relationships between 249 circulating metabolites and PIH. Inverse variance weighted, MR-egger, weight median, simple mode, and weighted mode methods were used for causal estimates. The exposure-to-outcome directionality was confirmed with the MR Steiger test. The Bayesian model averaging MR (MR-BMA) method was applied to detect the predominant causal metabolic traits with alignment for pleiotropy effects. In the primary analysis, analyzing 249 metabolites, we identified 25 causally linked to PIH, including 11 lipid-related traits and 6 associated with fatty acid (un)saturation. Importantly, MR-BMA analyses corroborated the total concentration of branched-chain amino acids(total-BCAA) to be the highest rank causal metabolite, followed by leucine (Leu), phospholipids to total lipids ratio in medium LDL (M-LDL-PL-pct), and Val (all P < 0.05). The directionality of causality predicted by univariable MR and MR-BMA for these metabolites remained consistent. This study highlights the causal connection between metabolites and PIH risk. It highlighted BCAAs as the strongest causal candidates warranting further investigation. Since PIH typically occurs in the second and third trimesters, extending these findings could inform earlier strategies to reduce its risk. Directed acyclic graph of the MR framework investigating the causal relationship between metabolites and PIH. MR: Mendelian randomization; GIVs: genetic instrument variables; SNPs: single-nucleotide polymorphism; IVW: inverse variance weighted; WM: weighted median; PIH: pregnancy-induced hypertension; SM: significant metabolite; MR-BMA: Bayesian model averaging MR.

Indexed as

Bayes TheoremHypertension, Pregnancy-InducedMendelian Randomization AnalysisBiomarkersFemaleHumansPregnancyBiomarkersBayesian modelBlood metabolitesLipidsMendelian randomizationPregnancy-induced hypertension

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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.