Last updated:
Author(s):
Guiyuan Han, Chon Lok Lei, Yu Shi, Jiajia Gao, Xiaoying Liu, Ke Peng, Yunpeng Cai, Pui Man Hoi, Yichong Li
Publish date:
20 April 2026
Journal:
Journal of Lipid Research
PubMed ID:
42019808

Abstract

BACKGROUND: Remnant cholesterol (RC) is increasingly recognized as an independent contributor to coronary heart disease (CHD) risk beyond low-density lipoprotein cholesterol (LDL-C). However, its causal roles, genetic determinants, tissue-specific regulation, and relevance across ancestrally diverse populations remain incompletely characterized.

METHODS: Associations between RC and incident CHD were evaluated in the UK Biobank employing Cox regression and restricted cubic splines models, including subgroup analyses by LDL-C levels. Causality was assessed using two-sample Mendelian randomization (MR) and colocalization using genome-wide summary statistics from UK Biobank and FinnGen. Findings were validated in a multi-ancestry dataset. Genetic regulatory mechanisms were explored using tissue-specific MR integrating expression quantitative trait locus. Lipid-wide MR was used to evaluate gene effects across multiple lipid traits. Comparison between identified genes and established lipid-modifying target genes was conducted.

RESULTS: RC showed a size-specific, LDL-C-independent association with CHD, which remained strong among individuals with normal LDL-C (<2.6 mmol/L). Multivariable MR confirmed a robust causal relationship. Colocalization identified shared signals at the PSRC1-CELSR2-SORT1 locus, with lead variants rs12740347 and rs646776. This cluster exhibited liver-specific inverse associations with CHD, pleiotropic effects on lipid traits, and stronger influence on RC than well-known targets such as HMGCR and PCSK9.

CONCLUSIONS: RC represents a potentially modifiable marker of CHD risk, especially in individuals with normal LDL-C. Hepatic expression of PSRC1-CELSR2-SORT1 protects against CHD via RC reduction, independent of LDL-C, supporting RC as promising target for CHD prevention.

Related projects

Progress in understanding the causes of major depressive disorder has been slow. Dividing depression into subtypes, a process called stratification, could ultimately lead to faster…

Institution:
University of Edinburgh, Great Britain

All projects