Dataset for a Multivariate Genome-Wide Association Study of Psycho-Cardiometabolic Multimorbidity

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UniversityofBath_DTA_FullEx_12August2021.pdf

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UniversityofBath_SOW1_FullEx_13August2021.pdf

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http://eprints.org/relation/isVersionOf https://researchdata.bath.ac.uk/id/document/16284 http://eprints.org/relation/isVolatileVersionOf https://researchdata.bath.ac.uk/id/document/16284 http://eprints.org/relation/issmallThumbnailVersionOf https://researchdata.bath.ac.uk/id/document/16284 16290 2 54622 document 16290 lightbox.jpg image/png b88e9ca011cb967ecbfbcb517d87b504 MD5 35169 2022-08-18 07:50:10 https://researchdata.bath.ac.uk/1179/8/lightbox.jpg 1179 8 8 image/png other Thumbnails conversion from other to thumbnail_lightbox en staffonly

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http://eprints.org/relation/isVersionOf https://researchdata.bath.ac.uk/id/document/16285 http://eprints.org/relation/isVolatileVersionOf https://researchdata.bath.ac.uk/id/document/16285 http://eprints.org/relation/issmallThumbnailVersionOf https://researchdata.bath.ac.uk/id/document/16285 17146 8 60797 document 17146 top_10000_SNPs.zip application/zip ef94df6c34687dceba2f2a10f1e9f673 MD5 1317422 2023-05-23 09:17:19 https://researchdata.bath.ac.uk/1179/16/top_10000_SNPs.zip 1179 16 16 application/zip other Summary statistics for the top 10,000 variants from the genome-wide association study of psycho-cardiometabolic multimorbidity (i.e., major depression, coronary artery disease, and type 2 diabetes). This folder contains two files: top 10,000 SNPs for the version with UK Biobank (PCM_multimorbidity_summary_stats_withUKBB_10000_SNPs.txt) and top 10,000 SNPs for the version without UK Biobank (PCM_multimorbidity_summary_stats_noUKBB_10000_SNPs.txt). en public cc_by_sa

top_10000_SNPs.zip

data 17147 7 60800 document 17147 summary-stats-with-UKBB.zip application/zip b1c826f8bbb6e7c85e891c16eec02997 MD5 900921731 2023-05-23 09:19:55 https://researchdata.bath.ac.uk/1179/17/summary-stats-with-UKBB.zip 1179 17 17 application/zip other Summary statistics from the genome-wide association study of psycho-cardiometabolic multimorbidity (i.e., major depression, coronary artery disease, and type 2 diabetes). Version with UK Biobank. This folder contains two files: full summary statistics version (PCM_multimorbidity_summary_stats_withUKBB.txt.gz) and summary statistics with heterogeneous SNPs removed (PCM_multimorbidity_summary_stats_withUKBB_non-het.txt.gz). Effective sample size = 562,507. en staffonly all_rights_reserved

summary-stats-with-UKBB.zip

data 17148 4 60808 document 17148 summary-stats-without-UKBB.zip application/zip 458c9ad455932713b29e2abbe8e23555 MD5 629960123 2023-05-23 09:41:21 https://researchdata.bath.ac.uk/1179/18/summary-stats-without-UKBB.zip 1179 18 18 application/zip other Summary statistics from the genome-wide association study of psycho-cardiometabolic multimorbidity (i.e., major depression, coronary artery disease, and type 2 diabetes). Version without UK Biobank. This folder contains two files: full summary statistics version (PCM_multimorbidity_summary_stats_noUKBB.txt.gz) and summary statistics with heterogeneous SNPs removed (PCM_multimorbidity_summary_stats_noUKBB_non-het.txt.gz). Effective sample size = 156,717. en staffonly all_rights_reserved

summary-stats-without-UKBB.zip

data 17149 2 60838 document 17149 Psycho-cardiometabolic-multimorbidity-scripts.zip application/zip ad340d8c665fadb949c3c6e3c1c08707 MD5 9799 2023-05-24 08:32:06 https://researchdata.bath.ac.uk/1179/19/Psycho-cardiometabolic-multimorbidity-scripts.zip 1179 19 19 application/zip other R scripts that underlie the analysis in the associated publication en public cc_by_sa

Psycho-cardiometabolic-multimorbidity-scripts.zip

code archive 11990 disk0/00/00/11/79 2023-07-03 12:32:07 2024-07-22 11:03:45 2023-07-03 12:32:07 data_collection show Baltramonaityte Vilte vb506@bath.ac.uk 0000-0002-9776-735X University of Bath TRUE Pingault Jean-Baptiste 0000-0003-2557-4716 University College London FALSE Cecil Charlotte A.M. 0000-0002-2389-5922 Erasmus University Medical Center FALSE Choudhary Priyanka 0000-0002-2420-4118 University of Oulu FALSE Järvelin Marjo-Riitta 0000-0002-2149-0630 Imperial College London FALSE Penninx Brenda W.J.H. 0000-0001-7779-9672 Vrije Universiteit Amsterdam FALSE Felix Janine F. 0000-0002-9801-5774 Erasmus University Medical Center FALSE Sebert Sylvain 0000-0001-6681-6983 University of Oulu FALSE Milaneschi Yuri 0000-0002-3697-6617 Vrije Universiteit Amsterdam FALSE Walton Esther E.Walton@bath.ac.uk 0000-0002-0935-2200 University of Bath FALSE Dataset for a Multivariate Genome-Wide Association Study of Psycho-Cardiometabolic Multimorbidity JN0010 dept_psy Multimorbidity, Coronary artery disease, Type 2 diabetes, Depression, GWAS, Summary statistics, Psycho-cardiometabolic, EarlyCause For a detailed description of both sets of statistics, please see the associated publication. Summary statistics include: - SNP = single nucleotide polymorphism (SNP); - CHR = chromosome; - BP = position; - MAF = minor allele frequency; - A1 = effect allele; - A2 = non-effect allele; - BETA = effect of the SNP on the common factor; - SE = standard error; - Z_Estimate = ratio of effect/SE; - P = p-value of Z_Estimate; - chisq = chi-square statistic, providing the heterogeneity estimate for that SNP (equivalent to the Q SNP index); - chisq_df = chi-square degrees of freedom; - chisq_pval = chi-square p-value; - concordant = indicates whether effect estimates from three input genome-wide association studies were directionally concordant (TRUE = all three estimates were concordant; FALSE = at least one estimate was not concordant) This dataset contains summary statistics from a multivariate genome-wide association study of major depression, coronary artery disease, and type 2 diabetes (i.e., psycho-cardiometabolic multimorbidity). There are two sets of summary statistics: version with UK Biobank (effective sample size = 562,507) and version without UK Biobank (effective sample size = 156,717). Summary statistics for non-heterogeneous variants are also provided (obtained by removing variants with Q SNP P < 5e-8 and directionally discordant univariate effect estimates). For a given single nucleotide polymorphism (SNP), the summary statistics include the chromosome; position; minor allele frequency; effect allele; non-effect allele; effect of the SNP on the common factor; standard error; ratio of effect/SE; p-value of Z_Estimate; chi-square statistic, providing the heterogeneity estimate for that SNP (equivalent to the Q SNP index); chi-square degrees of freedom; chi-square p-value; whether effect estimates from three input genome-wide association studies were directionally concordant. 2023-06-30 University of Bath restricted https://github.com/VilteBaltra/Psycho-cardiometabolic-multimorbidity GitHub repository containing the R scripts used RightsHolder 23andMe RightsHolder University of Bath Horizon 2020 Framework Programme https://doi.org/10.13039/100010661 848158 EarlyCause This dataset was created using genomic structural equation modeling (Genomic SEM) package in R. First, a common factor model was specified to capture the shared variance between major depression, coronary artery disease, and type 2 diabetes. The shared variance reflected the latent psycho-cardiometabolic multimorbidity factor. Subsequently, summary statistics for psycho-cardiometabolic multimorbidity were generated by regressing the latent factor on each SNP, resulting in 6,820,149 SNPs. Full details of the methodology may be found in the Methods section of the associated paper. When using multimorbidity-associated variants as genetic instruments in Mendelian randomization analysis we recommend to only use non-heterogeneous SNPs. At the minimum, we recommend removing variants with QSNP P < 5e-8 and directionally discordant univariate effect estimates (option 1 below), as done in the non-heterogenous summary statistics versions (PCM_multimorbidity_summary_stats_noUKBB_non-het.txt.gz and PCM_multimorbidity_summary_stats_withUKBB_non-het.txt.gz). To ensure your analysis captures multimorbidity between coronary artery disease, type 2 diabetes and major depression, you may also apply a more stringent threshold for removing heterogeneous variants (e.g., QSNP P < 5e-6; option 2 below). A sample code for implementing this in R is included below: ``` # load tidyverse package library(tidyverse) # read in summary statistics sumstats <- read.delim("PCM_multimorbidity_summary_stats_withUKBB_non-het.txt.gz") # Option 1: remove discordant variants with QSNP P < 5e-8 data_not_concordant <- sumstats %>% filter(concordant == "FALSE") mm_snp_remove <- sumstats %>% filter(SNP %in% data_not_concordant$SNP) %>% filter(chisq_pval < 0.00000005) sumstas_nonhet <- sumstas %>% filter(!SNP %in% mm_snp_remove$SNP) # save file write.table(sumstas_nonhet, file = “newfile.txt", quote =F, sep = "\t", row.names = F) # Option 2: remove variants with QSNP P < 5e-6 sumstas_nonhet <- sumstas %>% filter(chisq_pval < 0.000005) # save file write.table(sumstas_nonhet, file = “newfile.txt", quote =F, sep = "\t", row.names = F) ``` https://github.com/GenomicSEM/GenomicSEM/wiki/4.-Common-Factor-GWAS https://doi.org/10.1371/journal.pgen.1010508 en 1 10.15125/BATH-01179 https://doi.org/10.1371/journal.pgen.1010508 pub open request Due to licensing restrictions, only a subset of data is openly available from this repository. To access summary statistics for all SNPs associated with multimorbidity, a data transfer agreement is required with 23andMe (dataset-request@23andMe.com) before making a request from this repository.