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.

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41440-024-01787-4DOI Listing

Publication Analysis

Top Keywords

mendelian randomization
8
blood metabolites
8
pregnancy-induced hypertension
8
causal relationships
8
causal
6
bma-based mendelian
4
randomization identifies
4
identifies blood
4
metabolites
4
metabolites causal
4

Similar Publications

Background: Previous studies report that Hashimoto's thyroiditis (HT) may be associated with non-ischemic cardiomyopathy (NICM); However, the causal relationship remains to be elucidated. Here, we aimed to investigate the causal relationship between HT and NICM through Mendelian randomization (MR) and explore the potential mediating role of inflammatory cytokines within this association.

Methods: The bidirectional two-sample MR, multivariable MR and mediation MR analyses were conducted based on genome-wide association study summary datasets, and MR results were further supported by multiple sensitivity analysis methods.

View Article and Find Full Text PDF

Parkinson's disease (PD) is the second most common age-related neurodegenerative disease after Alzheimer's disease. Despite numerous studies, specific age-related factors remain unidentified. This study employed a multi-omics approach to investigate the link between PD and aging.

View Article and Find Full Text PDF

The COVID-19 pandemic has significantly impacted the quality of life (QoL) of individuals in China, affecting both their physical and mental well-being. This study aims to comprehensively analyze the factors influencing QoL in China during the pandemic. In 2022, we collected data using a self-developed questionnaire (dataset 2) and obtained dataset 1 from the 2021 China General Social Survey (CGSS).

View Article and Find Full Text PDF

The high comorbidity of major depressive disorder (MDD) with other diseases has been well-documented. However, the pairwise causal connections for MDD comorbid networks are poorly characterized. We performed Phenome-wide Mendelian randomization (MR) analyses to explore bidirectional causal associations between MDD (N = 807,553) and 877 common diseases from FinnGen datasets (N = 377,277).

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!