Evidence map›Paper›PMID 30571344›Full record

ArticleCirculation2018

Probing the Virtual Proteome to Identify Novel Disease Biomarkers.

Jonathan D Mosley, Mark D Benson, J Gustav Smith, Olle Melander, Debby Ngo, Christian M Shaffer, Jane F Ferguson, Matthew S Herzig, Catherine A McCarty, Christopher G Chute and 28 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Circulation, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 3 pooled it
2.7field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed, 3 syntheses or guidelines pooled it, 51 citations in OpenAlex.

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  20. Personalizing treatments for patients based on cardiovascular phenotyping.Expert review of precision medicine and drug development · 2022
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

38 authors at 3 institutions in 1 country.

Jonathan D MosleyDepartment of Medicine (J.D.M., C.M.S., J.F.F., J.C.D., T.J.W.), Vanderbilt University Medical Center, Nashville, TN.
Mark D BensonCardiovascular Division, Brigham and Women's Hospital, Boston, MA (M.D.B.).
J Gustav SmithMolecular Epidemiology and Cardiology, Clinical Sciences, Lund University and Skåne University Hospital, Malmö, Sweden (J.G.S., O.M.).
Olle MelanderMolecular Epidemiology and Cardiology, Clinical Sciences, Lund University and Skåne University Hospital, Malmö, Sweden (J.G.S., O.M.).
Debby NgoDepartment of Medicine and the Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston (D.N.).
Christian M ShafferDepartment of Medicine (J.D.M., C.M.S., J.F.F., J.C.D., T.J.W.), Vanderbilt University Medical Center, Nashville, TN.
Jane F FergusonDepartment of Medicine (J.D.M., C.M.S., J.F.F., J.C.D., T.J.W.), Vanderbilt University Medical Center, Nashville, TN.
Matthew S HerzigDivision of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA (M.D.B., M.S.H., R.E.G.).
Catherine A McCartyUniversity of Minnesota Medical School, Duluth Campus (C.A.M.).
Christopher G ChuteSchools of Medicine, Public Health, and Nursing, Johns Hopkins University, Baltimore, MD (C.G.C.).
Gail P JarvikDepartments of Medicine (J.P.J., A.S.G., M.R.P., E.B.L.), University of Washington, Seattle.
Adam S GordonDepartments of Medicine (J.P.J., A.S.G., M.R.P., E.B.L.), University of Washington, Seattle.
Melody R PalmerDepartments of Medicine (J.P.J., A.S.G., M.R.P., E.B.L.), University of Washington, Seattle.
David R CrosslinBiomedical Informatics and Medical Education (D.R.C.), University of Washington, Seattle.
Eric B LarsonDepartments of Medicine (J.P.J., A.S.G., M.R.P., E.B.L.), University of Washington, Seattle.
David S CarrellKaiser Permanente Washington Health Research Institute, Seattle, WA (E.B.L., D.S.C.).
Iftikhar J KulloDepartment of Cardiovascular Diseases, Mayo Clinic, Rochester, MN (I.J.K.).
Jennifer A PachecoCenter for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (J.A.P.).
Peggy L PeissigBiomedical Informatics Research Center (P.L.P., J.G.L.), Marshfield Clinic Research Institute, WI.
Murray H BrilliantCenter for Computational and Biomedical Informatics (M.H.B., T.E.K.), Marshfield Clinic Research Institute, WI.
Terrie E KitchnerCenter for Computational and Biomedical Informatics (M.H.B., T.E.K.), Marshfield Clinic Research Institute, WI.
James G LinnemanBiomedical Informatics Research Center (P.L.P., J.G.L.), Marshfield Clinic Research Institute, WI.
Bahram NamjouCincinnati Children's Hospital Medical Center and University of Cincinnati, OH (B.N.).
Marc S WilliamsGenomic Medicine Institute (M.S.W.), Geisinger Health System, Danville, PA.
Marylyn D RitchieDepartments of Bioinformatics and Genetics (M.D.R.), University of Pennsylvania, Philadelphia.
Kenneth M BorthwickBiomedical and Translational Informatics (K.M.B.), Geisinger Health System, Danville, PA.
Krzysztof KirylukDepartment of Medicine, College of Physicians and Surgeons, Columbia University, New York, NY (K.K.).
Frank D MentchCenter for Applied Genomics, Children's Hospital of Philadelphia, PA (F.D.M., P.M.S.).
Patrick M SleimanCenter for Applied Genomics, Children's Hospital of Philadelphia, PA (F.D.M., P.M.S.).
Elizabeth W KarlsonDepartment of Medicine, Division of Rheumatology, Immunology and Allergy, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (E.W.K.).
Shefali S VermaPerelman School of Medicine, Department of Genetics (S.S.V.), University of Pennsylvania, Philadelphia.
Yineng ZhuDepartment of Biostatistics, Boston University School of Public Health, MA (Y.Z., Q.Y.).
Ramachandran S VasanDepartment of Medicine, Boston University School of Medicine, MA (R.S.V.).
Qiong YangDepartment of Biostatistics, Boston University School of Public Health, MA (Y.Z., Q.Y.).
Josh C DennyDepartment of Medicine (J.D.M., C.M.S., J.F.F., J.C.D., T.J.W.), Vanderbilt University Medical Center, Nashville, TN.
Dan M RodenBiomedical Informatics (J.C.D., D.M.R.), Vanderbilt University Medical Center, Nashville, TN.
Robert E GersztenDivision of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA (M.D.B., M.S.H., R.E.G.).
Thomas J WangDepartment of Medicine (J.D.M., C.M.S., J.F.F., J.C.D., T.J.W.), Vanderbilt University Medical Center, Nashville, TN.
Vanderbilt University Medical Center · USBrigham and Women's Hospital · USNorthwestern University · US

Funding

Tumor Immunology and Microenvironment Research ProgramP30CA068485 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI STACIE B DUSETZINA · 1995 to 2026
$172.8M
The Vanderbilt Institute for Clinical and Translational Research (VICTR)UL1TR000445 · NCATS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI BERNARD, GORDON RAPHAEL · 2012 to 2016
$41.4M
Shop Module CoreP30EY008126 · NEI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI David J. Calkins · 1989 to 2026
$19.6M
Genomic Basis of Susceptibility to COVID-19 Infection and its ComplicationsU01HG006379 · NHGRI · MAYO CLINIC ROCHESTER · PI Richard R. Sharp · 2011 to 2026
$16.5M
MULTIDISCIPLINARY RESEARCH TRAINING IN CARDIOLOGYT32HL007208 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI Patrick Thomas Ellinor, David E Sosnovik · 1985 to 2026
$16.1M
Finding Genomic Profiles of COVID-19 Phenotypes from the EHRU01HG008685 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI ELIZABETH W KARLSON, Matthew S Lebo · 2015 to 2026
$13.6M
Variation, Function, and Disease Supplement ProgramU01HG008657 · NHGRI · UNIVERSITY OF WASHINGTON · PI David Russell Crosslin, Gail Pairitz Jarvik · 2015 to 2026
$13.4M
Understanding and preventing HLA-associated drug reactionsP50GM115305 · NIGMS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI PHILLIPS, ELIZABETH · 2015 to 2019
$13.0M
Proteomics of Cardiometabolic and Renal Traits in African AmericansR01HL133870 · NHLBI · UNIVERSITY OF MISSISSIPPI MED CTR · PI ROBERT E GERSZTEN · 2017 to 2026
$6.7M
From GWAS to PheWAS: Scanning the EMR Phenome for Gene-disease AssociationsR01LM010685 · NLM · VANDERBILT UNIVERSITY MEDICAL CENTER · PI BASTARACHE, LISA · 2011 to 2022
$6.3M
eMERGE Coordinating Center - Administrative SupplementU01HG006385 · NHGRI · VANDERBILT UNIVERSITY · PI HARRIS, PAUL A. · 2011 to 2014
$5.4M
Biorepository for Genomic Medicine in diverse CommunitiesU01HG006380 · NHGRI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI BOTTINGER, ERWIN P. · 2011 to 2015
$4.5M
American Heart Association-American Stroke Association 16FTF30130005NCATS NIH HHS UL1 TR000445NCI NIH HHS P30 CA068485NCRR NIH HHS S10 RR025141NEI NIH HHS P30 EY008126NHGRI NIH HHS U01 HG006378NHGRI NIH HHS U01 HG006379NHGRI NIH HHS U01 HG006380NHGRI NIH HHS U01 HG006382NHGRI NIH HHS U01 HG006385NHGRI NIH HHS U01 HG006388NHGRI NIH HHS U01 HG006389NHGRI NIH HHS U01 HG006828NHGRI NIH HHS U01 HG006830NHGRI NIH HHS U01 HG008657NHGRI NIH HHS U01 HG008685NHLBI NIH HHS R01 HL132320NHLBI NIH HHS R01 HL133870NHLBI NIH HHS T32 HL007208NIGMS NIH HHS P50 GM115305NLM NIH HHS R01 LM010685
6 · The paper itself

Abstract

backgroundProteomic approaches allow measurement of thousands of proteins in a single specimen, which can accelerate biomarker discovery. However, applying these technologies to massive biobanks is not currently feasible because of the practical barriers and costs of implementing such assays at scale. To overcome these challenges, we used a "virtual proteomic" approach, linking genetically predicted protein levels to clinical diagnoses in >40 000 individuals.

methodsWe used genome-wide association data from the Framingham Heart Study (n=759) to construct genetic predictors for 1129 plasma protein levels. We validated the genetic predictors for 268 proteins and used them to compute predicted protein levels in 41 288 genotyped individuals in the Electronic Medical Records and Genomics (eMERGE) cohort. We tested associations for each predicted protein with 1128 clinical phenotypes. Lead associations were validated with directly measured protein levels and either low-density lipoprotein cholesterol or subclinical atherosclerosis in the MDCS (Malmö Diet and Cancer Study; n=651).

resultsIn the virtual proteomic analysis in eMERGE, 55 proteins were associated with 89 distinct diagnoses at a false discovery rate q<0.1. Among these, 13 associations involved lipid (n=7) or atherosclerosis (n=6) phenotypes. We tested each association for validation in MDCS using directly measured protein levels. At Bonferroni-adjusted significance thresholds, levels of apolipoprotein E isoforms were associated with hyperlipidemia, and circulating C-type lectin domain family 1 member B and platelet-derived growth factor receptor-β predicted subclinical atherosclerosis. Odds ratios for carotid atherosclerosis were 1.31 (95% CI, 1.08-1.58; P=0.006) per 1-SD increment in C-type lectin domain family 1 member B and 0.79 (0.66-0.94; P=0.008) per 1-SD increment in platelet-derived growth factor receptor-β.

conclusionsWe demonstrate a biomarker discovery paradigm to identify candidate biomarkers of cardiovascular and other diseases.

Indexed as

Genome-Wide Association StudyAdultAgedAged, 80 and overBiomarkersCarotid Artery DiseasesFemaleGenotypeHumansLectins, C-TypeMaleMiddle AgedOdds RatioPhenotypePolymorphism, Single NucleotideProteomeBiomarkersCLEC1B protein, humanLectins, C-TypeProteomeReceptor, Platelet-Derived Growth Factor betaatherosclerosisbiomarkerselectronic health recordsproteomics

Identifiers

PMID30571344
PMCPMC8833190
OpenAlexW2899328785

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.