Associations between lipid parameters and depression with the moderating role of inflammation: Network analyses of 87,636 UK Biobank participants

Pingan Li; Haiping Zhang; Jianhua Ma; Jinqi Wang; Shiyun Lv; Xiaoyu Zhao; Xinghua Yang; Yanxia Luo; Lixin Tao; Xiuhua Guo; Bo Gao

doi:10.1016/j.psyneuen.2025.107543

Associations between lipid parameters and depression with the moderating role of inflammation: Network analyses of 87,636 UK Biobank participants

Psychoneuroendocrinology. 2025 Jul 9:180:107543. doi: 10.1016/j.psyneuen.2025.107543. Online ahead of print.

Authors

Pingan Li¹, Haiping Zhang², Jianhua Ma³, Jinqi Wang⁴, Shiyun Lv⁵, Xiaoyu Zhao⁶, Xinghua Yang⁷, Yanxia Luo⁸, Lixin Tao⁹, Xiuhua Guo¹⁰, Bo Gao¹¹

Affiliations

¹ Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing 100069, China. Electronic address: lipingan@mail.ccmu.edu.cn.
² Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing 100069, China. Electronic address: yeszhang09@163.com.
³ Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing 100069, China. Electronic address: mjh0122@mail.ccmu.edu.cn.
⁴ Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing 100069, China. Electronic address: wangjinqi@ccmu.edu.cn.
⁵ Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing 100069, China. Electronic address: lv_shiyun@163.com.
⁶ Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing 100069, China. Electronic address: zhaoxiaoyu@mail.ccmu.edu.cn.
⁷ Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing 100069, China. Electronic address: xinghuayang@ccmu.edu.cn.
⁸ Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing 100069, China. Electronic address: lyx100@ccmu.edu.cn.
⁹ Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing 100069, China. Electronic address: taolixin@ccmu.edu.cn.
¹⁰ Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing 100069, China. Electronic address: statguo@ccmu.edu.cn.
¹¹ Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing 100069, China. Electronic address: gaobo@ccmu.edu.cn.

PMID: 40652641
DOI: 10.1016/j.psyneuen.2025.107543

Abstract

Background: Studies investigating lipid-depression associations have reported inconsistent findings, and few have considered the interrelationships among lipid parameters. Additionally, the moderating role of inflammation in these associations remains unclear. This study aims to (1) assess lipid-depression associations after controlling for other lipid parameters, and (2) explore the moderating effect of inflammation.

Methods: The study included 87,636 participants from the UK Biobank. A pairwise mixed graphical model (MGM) network was constructed in the entire sample to examine the prospective associations between seven lipid parameters and depression. The moderating role of inflammation was explored by: (1) estimating pairwise MGM networks for groups stratified by high-sensitivity C-reactive protein (hs-CRP) levels, (2) conducting network comparison tests (NCTs), and (3) constructing moderated network models (MNMs).

Results: In the full-sample network, edges connecting triglycerides (TG, edge weight = 0.034), high-density lipoprotein cholesterol (HDL-C, edge weight = -0.011), low-density lipoprotein cholesterol (LDL-C, edge weight = -0.009), and lipoprotein(a) (Lp(a), edge weight = 0.012) with depression were identified. The non-elevated and elevated hs-CRP networks exhibited opposite signs for the Lp(a)-depression edge. In NCTs, HDL-C-depression and apolipoprotein A1 (Apo A1)-depression showed significant differences in edge weights. hs-CRP moderates the associations of HDL-C, Apo A1, and Lp(a) with depression in MNMs.

Conclusions: After controlling for other lipid parameters, TG and Lp(a) are positively, while HDL-C and LDL-C are negatively associated with depression in the overall study population. Inflammation moderates the associations of HDL-C, Apo A1, and Lp(a) with depression. Our study provides further evidence for the lipid-depression associations.

Keywords: Depression; High-sensitivity C-reactive protein; Inflammation; Lipid parameters; Moderation; Network analysis.