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. 2021 Oct 21;12(1):6120.
doi: 10.1038/s41467-021-25731-z.

Validation of lipid-related therapeutic targets for coronary heart disease prevention using human genetics

María Gordillo-Marañón  1 , Magdalena Zwierzyna  2   3 , Pimphen Charoen  2   4   5 , Fotios Drenos  2   6 , Sandesh Chopade  2   3 , Tina Shah  2   3 , Jorgen Engmann  2   3 , Nishi Chaturvedi  2   7 , Olia Papacosta  8 , Goya Wannamethee  8 , Andrew Wong  7 , Reecha Sofat  9 , Mika Kivimaki  10 , Jackie F Price  11 , Alun D Hughes  2   3   7 , Tom R Gaunt  12   13   14 , Deborah A Lawlor  12   13   14 , Anna Gaulton  15 , Aroon D Hingorani #  2   3 , Amand F Schmidt #  2   3   16 , Chris Finan #  2   3   16
Affiliations

Validation of lipid-related therapeutic targets for coronary heart disease prevention using human genetics

María Gordillo-Marañón et al. Nat Commun. .

Abstract

Drug target Mendelian randomization (MR) studies use DNA sequence variants in or near a gene encoding a drug target, that alter the target's expression or function, as a tool to anticipate the effect of drug action on the same target. Here we apply MR to prioritize drug targets for their causal relevance for coronary heart disease (CHD). The targets are further prioritized using independent replication, co-localization, protein expression profiles and data from the British National Formulary and clinicaltrials.gov. Out of the 341 drug targets identified through their association with blood lipids (HDL-C, LDL-C and triglycerides), we robustly prioritize 30 targets that might elicit beneficial effects in the prevention or treatment of CHD, including NPC1L1 and PCSK9, the targets of drugs used in CHD prevention. We discuss how this approach can be generalized to other targets, disease biomarkers and endpoints to help prioritize and validate targets during the drug development process.

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Conflict of interest statement

A.F.S. has received Servier funding for unrelated work. M.Z. conducted this research as an employee of BenevolentAI. Since completing the work M.Z. is now a full-time employee of GlaxoSmithKline.

Figures

Fig. 1
Fig. 1. HDL-C, CETP inhibitor, and CHD: genome-wide biomarker vs. drug target MR.
Forest plot of the HDL-C biomarker MR estimate (Holmes et al., 2015), drug target MR estimate of CETP level and function using HDL-C as a proxy (Schmidt et al., 2020), and odds ratio of anacetrapib clinical trial (HPS3/TIMI55–REVEAL Collaborative Group, 2017). OR odds ratio, CI confidence interval, SD standard deviation.
Fig. 2
Fig. 2. Discovery drug target MR estimates on CHD.
Analyses were performed using genetic associations with LDL-C, HDL-C, and TG from the Global Lipid Genetic Consortium (GLGC) with CHD events from the CardiogramPlusC4D Consortium. Drug targets are grouped by clinical phase according to the ChEMBL database. Blue indicates a beneficial effect on CHD risk and red a detrimental effect per SD difference with respect to the indicated lipid sub-fraction. Significant estimates are indicated with an asterisk (*). Co-localization of genetic effects on the relevant lipid sub-fraction and CHD at the same locus is indicated by a square around the cell.
Fig. 3
Fig. 3. Replication of drug target MR findings.
The discovery and replication analyses used different data sources for both exposure and outcome. Totally, 145 replication MR analyses were performed in which the gene boundaries included genetic associations exceeding the pre-specified significance threshold (P value ≤ 1 × 10−4).
Fig. 4
Fig. 4. Prioritized target: lipoprotein lipase (LPL).
a Genetic associations at the locus (±50 kbp) in black vs. genome-wide associations (gray, P value < 1 × 10−6 based on two-sided z-tests). The x-axis shows the per allele effect on the corresponding lipid expressed as mean difference (MD) from GLGC and the y-axis indicates the per allele effect on CHD expressed as log odds ratios (OR) from CardiogramPlusC4D. The marker size indicates the significance of the association with the lipid sub-fraction (P value). b Univariable and multivariable (drug target) cis-MR results presented as OR and 95% confidence intervals with lipid exposure (n = 188,577 individuals) and CHD outcome (n = 60,801 cases and 123,504 controls). An asterisk (*) indicates the MR estimates as being replicated, and a dagger (†) that the lipid effect and CHD signals are co-localized. c. Disease associations at the locus with 103 clinical endpoints from UK Biobank and GWAS Consortia.
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