Examining the link between 179 lipid species and 7 diseases using genetic predictors

Abstract

Background: Genome-wide association studies of lipid species have identified several loci shared with various diseases, however, the relationship between lipid species and disease risk remains poorly understood. Here we investigated whether the plasma levels of lipid species are causally linked to disease risk.

Methods: We built genetic predictors of 179 lipid species, measured in 7174 Finnish individuals, by utilising either 11 high-impact genomic loci or genome-wide polygenic scores (PGS). We assessed the impact of the lipid species on seven diseases by performing disease association across FinnGen (n = 500,348), UK Biobank (n = 420,531), and Generation Scotland (n = 20,032). We performed univariable Mendelian randomisation (MR) and multivariable MR (MVMR) analyses to examine whether lipid species impact disease risk independently of standard lipids.

Findings: PGS explained >4% of the variance for 34 lipid species but variants outside the high-impact loci had only a marginal contribution. Variants within the high-impact loci showed association with all seven diseases. MVMR supported a causal role of ApoB in ischaemic heart disease after accounting for lipid species. Phosphatidylethanolamine-increasing LIPC variants seemed to lower age-related macular degeneration risk independently of HDL-cholesterol. MVMR suggested a protective effect of four lipid species containing arachidonic acid on cholelithiasis risk independently of Total Cholesterol.

Interpretation: Our study demonstrates how genetic predictors of lipid species can be utilised to gain insights into disease risk. We report potential links between lipid species and age-related macular degeneration and cholelithiasis risk, which can be explored for their utility in disease risk prediction and therapy.

Funding: The funders had no role in the study design, data analyses, interpretation, or writing of this article.

Keywords: Disease risk; GWAS; Lipidomics; Mendelian randomisation; PGS.

Fig. 1

Study design. The 179 lipid species belong to 13 lipid classes and 4 categories. Lipid class, category, SwissLipidsName, and GWAS sample size of the lipid species are listed in Supplementary Table S1.

Fig. 2

Regional heritability (h²) of lipid species for genome-wide significant loci estimated by FINEMAP. a: glycerophospholipids, b: glycerolipids, sphingolipids, and sterols. High-impact loci (h² > 2% for at least one lipid species) are coloured, and the other genome-wide significant loci not among the high-impact loci are depicted as grey. Heritability estimation was performed with FINEMAP using summary statistics of GWAS from n = 7174 biologically independent samples. CE cholesteryl ester, Cer ceramide, DAG diacylglycerol, LPC lysophosphatidylcholine, LPE, lysophosphatidylethanolamine, PC phosphatidylcholine, PCO, phosphatidylcholine-ether, PE phosphatidylethanolamine, PEO phosphatidylethanolamine-ether, PI phosphatidylinositol, SM sphingomyelin, TAG triacylglycerol.

Fig. 3

Comparison of heritability (h²) estimates of lead variant and regional h² estimates for high-impact loci named at the top. Error bars represent 95% CI. Only the trait-locus combinations for which regional h² is located outside the 95% CI of lead variant h² are shown. Heritability estimation was performed with FINEMAP using summary statistics of GWAS from n = 7174 biologically independent samples.

Fig. 4

Variance explained (R²) by PGS for 25 lipid species reaching R² > 4% with PRS-CS in the FINRISK validation cohort. R² for both the full PGS calculation and for the calculation without high-impact loci is given. PGS weights were calculated using summary statistics of GeneRISK GWAS from n = 7174 biologically independent samples. Scores were validated using n = 1032 biologically independent samples from the FINRISK cohort.

Fig. 5

Disease associations for high-impact loci. Columns indicate independent signals at the 11 high-impact loci. Rows represent the seven diseases. Coloured tiles depict that at least one lead variant or FINEMAP representative variant from a genome-wide significant lipid species association reaches a specific P-value threshold in a disease endpoint GWAS. Two-sided P-values were calculated using a linear-mixed-model. Asterisks denote that the threshold 0.05/7 = 7.14e-3 (corrected for the number of diseases) is reached in multiple cohorts. AD: Alzheimer’s disease, AMD: age-related macular degeneration, Hyperchol: hypercholesterolaemia, IHD: ischaemic heart disease, MASLD: Metabolic dysfunction-associated steatotic liver disease, T2D: type 2 diabetes.

Fig. 6

Forest plots of effect sizes of IVW-MR for IHD, AMD, and cholelithiasis. Univariable MR results are shown when P < 2.3e-3 (0.05/22) in IVW-MR, P < 0.05 for all MR methods, and the effect direction is consistent for all methods. Univariable MR results of the standard lipid previously suggested to be causal for the disease are shown (ApoB for IHD, HDL-C for AMD, and TC for cholelithiasis). The pairwise Pearson correlation of the exposure with this standard lipid is listed. Each multivariable MR analysis contains as exposures the standard lipid (Exposure 1, in red) and a lipid species (Exposure 2, in black). Multivariable MR results are shown for the lipid species reaching significance in univariable MR.