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Decoding Anxiety: Plasma Lipids and Proteins as Causal Agents.

Jul 2026 · Behavioural Brain Research · Vol 514, pp. 116402 · 0 citations · 77 references
Medicine

TL;DR

This work leveraged two-sample Mendelian randomization to systematically evaluate the causal effects of 179 plasma lipid species and 4,907 plasma proteins on anxiety disorders, using two large-scale independent GWAS datasets for replication and identified three lipids with robust causal effects.

Abstract

Anxiety disorders represent a major psychiatric burden, yet their molecular underpinnings remain poorly understood. While observational studies have linked circulating lipids and proteins to mental health, causal inference is hampered by confounding and reverse causation. Here, we leveraged two-sample Mendelian randomization (MR) to systematically evaluate the causal effects of 179 plasma lipid species and 4,907 plasma proteins on anxiety disorders, using two large-scale independent GWAS datasets for replication. Significant findings from the primary inverse variance weighted analysis were validated using Bayesian Weighted MR and MR Robust Adjusted Profile Score methods to mitigate potential pleiotropy. Sensitivity analyses and reverse MR assessed robustness and directionality. Mediation analyses further explored whether protein signatures mediate lipid-anxiety associations. We identified three lipids with robust causal effects, with sterol ester (27:1/20:5) consistently conferring a protective effect across both cohorts. Additionally, 31 proteins showed significant causal links to anxiety. Notably, the protective effect of sterol ester (27:1/20:5) was partially mediated by the upregulation of SERPINA4 and ICT1, both of which exhibited protective associations. Our findings provide genetic evidence for causal roles of the plasma lipidome and proteome in anxiety disorders, and unveil a specific lipid-protein-anxiety pathway that may offer novel biomarkers and therapeutic targets. These results underscore the value of integrating multi-omic MR to dissect psychiatric disease mechanisms.

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