Additional file 1 of Sex and statin-related genetic associations at the PCSK9 gene locus: results of genome-wide association meta-analysis
Creators: name: Pott, Janne
name: Kheirkhah, Azin
name: Gadin, Jesper R.
name: Kleber, Marcus E.
name: Delgado, Graciela E.
name: Kirsten, Holger
name: Forer, Lukas
name: Hauck, Stefanie M.
name: Burkhardt, Ralph
name: Scharnagl, Hubert
name: Loeffler, Markus
name: März, Winfried
name: Thiery, Joachim
name: Gieger, Christian
name: Peters, Annette
name: Silveira, Angela
name: Hooft, Ferdinand van’t
name: Kronenberg, Florian
name: Scholz, Markus
Publisher: name: figshare
Year: 2024
Subjects: subject: Genetics
subject: FOS: Biological sciences

description: Additional file 1: Table S1. Study description. For each study, we report the most relevant parameters regarding our analysis. This includes description of PCSK9 measurement, covariable summary, genotyping information and GWAS tools and adjustment models. Table S2. Overview of sample sizes, SNP numbers and inflation factor per subgroup. For each subgroup, we report the number of valid SNPs after filtering for MAF, imputation info score and heterogeneity, the maximal number of studies available and the minimum and maximum sample size. The inflation factor λGC was estimated on the valid SNPs. Table S3. Overview of all associated loci (p &lt; 1 x 10-6). Here we list all loci with at least one significant association. The default range of a region was 1MB (lead SNPs position +/- 500 kB), but in case of overlapping regions we used the combined range. Loci were considered valid if there were 3 or more SNPs associated within the region. Statistics are given for the best subgroup only. Table S4a. Annotation of all associated SNPs at valid loci (p&lt;1x10−6 and 3 or more associated SNPs). For all SNPs, we report cytoband, SNP information (effect allele, EA; other allele, OA; EA frequency, EAF, and info score), compact gene information (more details in S4b-d), and statistics with all PCSK9 subgroups. Table S4b. Look-up of GWAS Catalogue entries of lead SNPs and their LD proxies. We searched the GWAS Catalogue for entries of the lead SNPs or their LD proxies (LD r2&gt;0.3) and report here the corresponding SNP, pairwise LD, reported genes and GWAS publication. Table S4c. Look-up of eQTLs of lead SNPs and their LD proxies. We searched publicly available eQTL databases for entries of the lead SNPs or their LD proxies (LD r2&gt;0.3) and report here the corresponding SNP, pairwise LD, reported genes, tissues, and eQTL publication. Table S4d. Look-up of proximate genes of lead SNPs. We report here all genes within 250 kB of the lead SNPs with the gene description, distance to the lead SNP, and gene position and orientation. Table S5a. Results of GCTA COJO select at PCSK9 gene locus (best SNP per subgroup). We searched for independent signals in each subgroup and report here the GWAS effects (column I-K) and the joint effects using LIFE as reference data (column M-P). Table S5b. Results of GCTA COJO joint at PCSK9 gene locus (same four independent SNPs for all subgroups). After selecting four independent SNPs out of the 7 selected SNPs, we estimated the joint effect of these four SNPs in all eight subgroups. The original GWAS effects are given in column F-H, while the joint effects are given in column M-O. Table S6a. Results of interaction test of all independent SNPs. Each independent SNP was tested for sex- and statin-interaction. We compared with respect to the best-associated phenotype. In more detail, if the best subgroup was statin-free males, then the sex-interaction was between statin-free males and females, and the statin-interaction was between statin-free and -treated males. Respective subgroups are given in columns O and U. Table S6b. Results of interaction test of all associated SNPs at the PCSK9 gene locus. Each associated SNP at PCSK9 was tested for sex- and statin-interaction. We compared with respect to the best-associated phenotype. In more detail, if the best subgroup was statin-free males, then the sex-interaction was between statin-free males and females, and the statin-interaction was between statin-free and -treated males. Respective subgroups are given in columns O and U. Table S7a. Results of colocalization analysis between the PCSK9 subgroups. We compared the association signals between the eight subgroups. For PCSK9, we tested all combinations, as all eight subgroups were associated. For the other loci, we only tested the best subgroup and their complements as in the interaction test. The two groups to compare are given in columns B and E. The five hypothesis are as follows: H0: no signal in either group. H1: only a signal in group 1. H2: only a signal in group 2. H3: signal in both groups but no colocalization. H4: signal in both groups and colocalization. Table S7b. Results of colocalization analysis between PCSK9 subgroups and gene expression. We compared the association signals of the eight subgroups with eQTL associations obtain from GTEx v8. For PCSK9, we tested also the conditional statistics. The two groups to compare are given in columns B and C. The five hypothesis are as follows: H0: no signal in either group. H1: only a signal in group 1. H2: only a signal in group 2. H3: signal in both groups but no colocalization. H4: signal in both groups and colocalization. Table S7c. Results of colocalization analysis between PCSK9 subgroups and other GWAS traits. We compared the association signals of the eight subgroups with other GWAS studies (lipids from GLGC, CAD, and sleep duration. For PCSK9, we tested also the conditional statistics. The two groups to compare are given in columns B and D. The five hypothesis are as follows: H0: no signal in either group. H1: only a signal in group 1. H2: only a signal in group 2. H3: signal in both groups but no colocalization. H4: signal in both groups and colocalization. Table 8a. Instruments used in the Mendelian Randomization (MR) analysis. In the MR, we used the same four SNPs in all eight subgroups. Here we report first the PCSK9 statistics from our GWAS including the F-statistic for each SNP, which is an indicator for instrument strength. LDL-C statistics from the stratified UKBB analysis and the Wald ratio for each SNP are added. Table 8b. Results of Mendelian Randomization analysis. For each subgroup, we estimated the inverse-variance weighted causal meta-effect of PCSK9 on LDL-C, and the MR-egger estimates for causal effect and intercept. For both methods, the heterogeneity is given by Cochran’s Q. Besides the method using all four instruments we list here the “leave-one-out” models using only 3 of 4 instruments. Table 8c. Results of interaction test of causal estimates. We used the IVW estimates of Table S8b to compare the causal estimates between the sexes and statin-treatment. Columns G and K indicate the compared groups.