Integrative analysis of the plasma proteome and polygenic risk of cardiometabolic diseases.

"the interval cohort data are available via the european genome-phenome archive with study accession no egas00001002555 . code availability the code used to generate the results of this study along with a detailed list of software and versions is available on github ( https://github com/sritchie73/cardiometabolic_prs_plasma_proteome/ ) which is permanently archived by zenodo 70 at 10 5281/zenodo 4762747. the interval cohort consists of approximately 50000 adult blood donors in england of which 3087 participants have linked electronic hospital records imputed genome-wide genotypes and quantitative levels of 3438 plasma proteins (supplementary data 1 and 2 ).; a curated information sheet for all 4034 aptamers is provided in supplementary data 1 .; the distributions of aptamer levels and associations with covariates before and after quality control are given in supplementary data 2 .; the pqtls used for each protein were (1) conditionally independent pqtls mapped in interval and published by sun et al which included both cis -pqtls (within 1 mb of the encoding gene) and trans -pqtls passing the trans significance threshold of p < 1 5 x 10 -11 ; (2) trans -pqtls with p < 1 5 x 10 -11 (lead variant only) for proteins not published in sun et al (b2m dusp26 and ftmt); and (3) hierarchically significant cis -pqtls (lead variant only) mapped in this study (supplementary data 4 and supplementary information ) for proteins without cis -pqtls passing the trans -pqtl significance threshold above (acy1 adipoq apoe cst3 gpd1 ptpru shbg and ust).; supplementary data supplementary data 1-4.; full summary statistics including exact p-values are detailed in supplementary data 3 b for linear regression tests on y-axes and in supplementary data 3 a for linear regression tests on x-axes d) compares protein levels quantified by the somalogic platform (x-axes) to protein levels quantified by the olink t96 platform (y-axes) after two years of follow-up in n = 646 interval participants e) compares protein levels quantified by the olink t96 platform (x-axes) to protein levels quantified by the olink explore platform (y-axes) in n = 418 interval participants f) compares pgs-protein associations from fig 1b in n = 3087 interval participants (x-axes) to pgs-protein associations (1) additionally adjusted for circadian effects (time of day of blood draw) (2) additionally adjusted for seasonal effects (date of blood draw) (3) when including 87 additional participants with prevalent cardiometabolic disease (n = 3174 on y-axis) and (4) when adjusting for bmi (n = 3072 participants with non-missing bmi on y-axis).; full summary statistics including exact p-values in these sensitivity analyses are detailed in supplementary data 3 c g) for the six proteins whose association with t2d pgs was attenuated by adjustment for bmi (p > 0 05; extended data fig 6f) gives from mediation analysis the estimated effect of t2d pgs on the protein levels through bmi (standard deviation change in protein levels through bmi per standard deviation increase in t2d pgs) percentage of t2d pgs to protein levels mediated by bmi and the estimated effect of t2d pgs on protein levels independent of bmi in n = 3072 interval participants.; full summary statistics including exact two-sided p-values for these tests are detailed in supplementary data 3 e .; full summary statistics including exact two-sided p-values for these tests are detailed in supplementary data 3 f .; summary statistics for all statistical tests are available in supplementary data 3 ; the additional cis -pqtls mapped in this study are provided in supplementary data 4 . data sharing agreement reference no. dars-nic-156334"

"code availability the code used to generate the results of this study along with a detailed list of software and versions is available on github ( https://github com/sritchie73/cardiometabolic_prs_plasma_proteome/ ) which is permanently archived by zenodo 70 at 10 5281/zenodo 4762747."

"Competing interests Several authors are now employed by or run pharmaceutical companies. All significant contributions to this study were made before these roles and the named companies had no role in the study. M.A. is an employee of AstraZeneca. P.S. is an employee of Roche. J.M. is an employee of Genomics PLC. G.A. is an employee of CSL Limited. S.K. is the chief executive officer of Verve Therapeutics. The other authors declare no competing interests."

"Participants in the INTERVAL randomized controlled trial were recruited with the active collaboration of NHS Blood and Transplant (www.nhsbt.nhs.uk), which has supported fieldwork and other elements of the trial. DNA extraction and genotyping were co-funded by the National Institute for Health Research (NIHR), the NIHR BioResource (http://bioresource.nihr.ac.uk) and the NIHR Cambridge Biomedical Research Centre (BRC) (no. BRC-1215-20014). Olink Proteomics assays were funded by Biogen. SomaLogic assays were funded by Merck and the NIHR Cambridge BRC (no. BRC-1215-20014). The academic coordinating centre for INTERVAL was supported by core funding from the NIHR Blood and Transplant Research Unit in Donor Health and Genomics (no. NIHR BTRU-2014-10024), UK Medical Research Council (MRC) (no. MR/L003120/1), British Heart Foundation (nos SP/09/002, RG/13/13/30194 and RG/18/13/33946) and the NIHR Cambridge BRC (no. BRC-1215-20014). A complete list of the investigators and contributors to the INTERVAL trial is provided in ref. 25. The academic coordinating centre thanks blood donor centre staff and blood donors for participating in the INTERVAL trial. This work was supported by Health Data Research UK, which is funded by the UK MRC, Engineering and Physical Sciences Research Council (EPSRC), Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation and Wellcome. This study was also supported by the Victorian Government’s Operational Infrastructure Support programme. This work was performed using resources provided by the Cambridge Service for Data Driven Discovery operated by the University of Cambridge Research Computing Service (https://www.hpc.cam.ac.uk/high-performance-computing), provided by Dell EMC and Intel using tier-2 funding from the EPSRC (capital grant no. EP/P020259/1), and DiRAC funding from the Science and Technology Facilities Council (www.dirac.ac.uk). This work uses data provided by patients and collected by the NHS and Public Health England as part of their care and support. Data on hospital episode statistics, mortality and cancer registration were obtained from NHS Digital (data sharing agreement reference no. DARS-NIC-156334-711SX). S.C.R. and J.M. were funded by the NIHR Cambridge BRC (no. BRC-1215-20014). S.A.L. is supported by a Canadian Institutes of Health Research postdoctoral fellowship (no. MFE-171279). G.A. was supported by a National Health and Medical Research Council of Australia Early Career Fellowship (no. 1090462). S.B. is supported by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (no. 204623/Z/16/Z). A.V.K. was supported by grants from the National Human Genome Research Institute (award nos 1K08HG010155 and 5UM1HG008895), an institutional grant from the Broad Institute of MIT and Harvard (variant2function) and a Hassenfeld Scholar Award from Massachusetts General Hospital. J.D. holds a British Heart Foundation Professorship and an NIHR Senior Investigator Award. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. The views expressed in this manuscript are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care."