Multi-ancestry genome-wide analysis of coronary artery calcification identifies novel loci, functional pathways, and druggable targets

Background

Collaboration for mapping targets from the CHARGE Consortium 1000G GWAS on coronary artery calcification (CAC) to the carotid plaque data in the Athero-Express Biobank Study with Maryam Kavousi, Maxime Bos, Clint L. Miller, and Pat Peyser.

Athero-Express Biobank Study

We have bulk RNAseq (n = 635 samples) and single-cell RNAseq data, genome-wide methylation (Illumina 450K) in n ± 600, as well as overlapping genetic data for ±2,100 individuals with extensive histological plaque characterisation. We will address the following questions:

Gene expression correlated to characteristics of plaques?
Where target genes expressed, which cell types?
Are any of the variants associated to plaque characteristics?

Methods

Mapping genes to single cells

We will use the last dataset from the scRNAseq data, including 35 individuals, to project target genes.

Genetic analyses

For the genetic analyses we will perform regression analyses adjusted for age, sex (where applicable) and principal components. So, we will apply the following model:

model 1: phenotype ~ age + sex + chip-used + PC1 + PC2 + year-of-surgery

phenotypes are:

calcification, coded Calc.bin no/minor vs. moderate/heavy staining
collagen, coded Collagen.bin no/minor vs. moderate/heavy staining
fat10, coded Fat.bin_10 no/<10% fat vs. >10% fat
fat40, coded Fat.bin_40 no/<40% fat vs. >40% fat
intraplaque hemorrhage, coded IPH.bin no vs. yes
macrophages (CD68), coded macmean0 mean of computer-assisted calculation CD68⁺ region of interest
smooth muscle cells (alpha-actin), coded smcmean0 mean of computer-assisted calculation SMA⁺ region of interest
intraplaque vessel density (CD34), coded vessel_density manually counted CD34⁺ cells per 3-4 hotspots
mast cells, coded Mast_cells_plaque manually counted mast cell tryptase⁺ cells (https://academic.oup.com/eurheartj/article/34/48/3699/484981)
neutrophils (CD66b), coded neutrophils manually counted CD66b⁺ cells (https://pubmed.ncbi.nlm.nih.gov/20595650/)

Continuous variables were inverse-rank normal transformated, indicated by _rankNorm.

Figure 1: Genotyped individuals in the Athero-Express Biobank Study

Gene expression

Whole-plaque RNAseq

For the expression analysis we used carotid plaque-derived bulk RNAseq data and queried it for the gene list. Below a graph showing the overall expression of the genes (not all are in the data) compared to the mean expression of 1,000 randomly picked genes.

Figure 2: Overall expression of target genes in carotid plaques from the Athero-Express Biobank Study

Where do I start?

You can load this project in RStudio by opening the file called 'CHARGE_1000G_CAC.Rproj'.

Project structure

CHARGE_1000G_CAC.Rmd
bulkRNAseq.Rmd
scRNAseq.Rmd
Parsing_GWASSumStats.Rmd
RegionalAssociationPlots.Rmd
PolarMorphism.Rmd

File	Description	Usage
README.md	Description of project	Human editable
LICENSE	User permissions	Read only
.worcs	WORCS metadata YAML	Read only
renv.lock	Reproducible R environment	Read only
renv	Reproducible R directory	Read only
BASELINE	Baseline tables directory	Human editable
COLOC_EA_vs_AA	Colocalization results directory	Human editable
CredibleSets	Credible sets as calculated and used	Human editable
images	Images directory	Human editable
OUTPUT	Generic output directory	Human editable
PLOTS	Generic plot directory	Human editable
PolarMorphism	PolarMorphism results directory	Human editable
RACER	Racer output directory	Human editable
RACER_AA	Racer African-American (AA) only output directory	Human editable
RACER_EA_vs_AA	Racer European-AA output directory	Human editable
scripts	Script to process some things	Human editable
SNP	SNP analyses scripts and results	Human editable
targets	Variant and gene target directory	Human editable
"1. CHARGE_1000G_CAC.Rmd"	Setting up work, including baseline, for AE	Human editable
"2. bulkRNAseq.Rmd"	Bulk RNAseq analyses in AE (not used)	Human editable
"3. scRNAseq.Rmd"	Single-cell RNAseq analyses in AE (not used)	Human editable
"4. Parsing_GWASSumStats.Rmd"	Parsing GWAS summary statistics for other analyses	Human editable
"5. RegionalAssociationPlots.Rmd"	Regional association plots, mirror and scatter, colocalization plots	Human editable
"6. PolarMorphism.Rmd"	Execute genome-wide overlap-analysis using PolarMorphism	Human editable
CHARGE_1000G_CAC	Script to process raw data	Human editable
CHARGE_1000G_CAC.Rproj	Project file	Loads project

Reproducibility

This project uses the Workflow for Open Reproducible Code in Science (WORCS) to ensure transparency and reproducibility. The workflow is designed to meet the principles of Open Science throughout a research project.

To learn how WORCS helps researchers meet the TOP-guidelines and FAIR principles, read the preprint at https://osf.io/zcvbs/

WORCS: Advice for authors

To get started with worcs, see the setup vignette
For detailed information about the steps of the WORCS workflow, see the workflow vignette

WORCS: Advice for readers

Please refer to the vignette on reproducing a WORCS project for step by step advice.

Acknowledgements

Dr. Sander W. van der Laan is funded through grants from the Netherlands CardioVascular Research Initiative of the Netherlands Heart Foundation (CVON 2011/B019 and CVON 2017-20: Generating the best evidence-based pharmaceutical targets for atherosclerosis [GENIUS I&II]). We are thankful for the support of the ERA-CVD program ‘druggable-MI-targets’ (grant number: 01KL1802), the EU H2020 TO_AITION (grant number: 848146), and the Leducq Fondation ‘PlaqOmics’.

Plaque samples are derived from carotid endarterectomies as part of the Athero-Express Biobank Study which is an ongoing study in the UMC Utrecht.

The framework was based on the WORCS package.

Changes log

Version:      v1.3
Last update:  2023-05-05
Written by:   Sander W. van der Laan (s.w.vanderlaan-2[at]umcutrecht.nl).
Description:  Script to get some Athero-Express Biobank Study baseline characteristics.
Minimum requirements: R version 3.4.3 (2017-06-30) -- 'Single Candle', Mac OS X El Capitan

Changes log
* v1.3.0 Fixed an issue with LD r2 plotting. Plus cleaned up project.
* v1.2.0 Cleanup of project. Re-initialize and snapshot renv. Also added colocalization between ancestries. 
* v1.1.0 Rename. Cleaning up of project (archiving/removing unused code and results).
* v1.0.7 Update to the count data.
* v1.0.6 Update to WORCS framework.
* v1.0.6 Update code and fix coding of plaque vulnerability index (PVI) to work with SNPTEST.
* v1.0.5 Updates to the gene list.
* v1.0.4 Updates to the gene list.
* v1.0.3 Update to the gene list.
* v1.0.2 Updated baseline characteristics information. Update GWASToolKit preparation. Added more candidate SNPs to look at. Updated some variable names. 
* v1.0.1 Add an additional phenotype.
* v1.0.0 Initial version. Fixed baseline table, added codes, and results. Created sample-files.

The MIT License (MIT)

Copyright (c) 1979-2022 Sander W. van der Laan | s.w.vanderlaan [at] gmail [dot] com.

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Reference: http://opensource.org.

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