{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T16:36:17Z","timestamp":1789662977961,"version":"4.0.1"},"reference-count":38,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"3","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["Circulation"],"published-print":{"date-parts":[[2022,1,18]]},"abstract":"<jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>Whereas several interventions can effectively lower lipid levels in people at risk for atherosclerotic cardiovascular disease (ASCVD), cardiovascular event risks remain, suggesting an unmet medical need to identify factors contributing to cardiovascular event risk. Monocytes and macrophages play central roles in atherosclerosis, but studies have yet to provide a detailed view of macrophage populations involved in increased ASCVD risk.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>A novel macrophage foaming analytics tool, AtheroSpectrum, was developed using 2 quantitative indices depicting lipid metabolism and the inflammatory status of macrophages. A machine learning algorithm was developed to analyze gene expression patterns in the peripheral monocyte transcriptome of MESA participants (Multi-Ethnic Study of Atherosclerosis; set 1; n=911). A list of 30 genes was generated and integrated with traditional risk factors to create an ASCVD risk prediction model (30-gene cardiovascular disease risk score [CR-30]), which was subsequently validated in the remaining MESA participants (set 2; n=228); performance of CR-30 was also tested in 2 independent human atherosclerotic tissue transcriptome data sets (GTEx [Genotype\u2013Tissue Expression] and GSE43292).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>\n                      Using single-cell transcriptomic profiles (GSE97310, GSE116240, GSE97941, and FR-FCM-Z23S), AtheroSpectrum detected 2 distinct programs in plaque macrophages\u2014homeostatic foaming and inflammatory pathogenic foaming\u2014the latter of which was positively associated with severity of atherosclerosis in multiple studies. A pool of 2209 pathogenic foaming genes was extracted and screened to select a subset of 30 genes correlated with cardiovascular event in MESA set 1. A cardiovascular disease risk score model (CR-30) was then developed by incorporating this gene set with traditional variables sensitive to cardiovascular event in MESA set 1 after cross-validation generalizability analysis. The performance of CR-30 was then tested in MESA set 2 (\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =2.60\u00d710\n                      <jats:sup>\u22124<\/jats:sup>\n                      ; area under the receiver operating characteristic curve, 0.742) and 2 independent data sets (GTEx:\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =7.32\u00d710\n                      <jats:sup>\u201317<\/jats:sup>\n                      ; area under the receiver operating characteristic curve, 0.664; GSE43292:\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =7.04\u00d710\n                      <jats:sup>\u22122<\/jats:sup>\n                      ; area under the receiver operating characteristic curve, 0.633). Model sensitivity tests confirmed the contribution of the 30-gene panel to the prediction model (likelihood ratio test;\n                      <jats:italic toggle=\"yes\">df<\/jats:italic>\n                      =31,\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =0.03).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>Our novel computational program (AtheroSpectrum) identified a specific gene expression profile associated with inflammatory macrophage foam cells. A subset of 30 genes expressed in circulating monocytes jointly contributed to prediction of symptomatic atherosclerotic vascular disease. Incorporating a pathogenic foaming gene set with known risk factors can significantly strengthen the power to predict ASCVD risk. Our programs may facilitate both mechanistic investigations and development of therapeutic and prognostic strategies for ASCVD risk.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1161\/circulationaha.121.054285","type":"journal-article","created":{"date-parts":[[2021,12,16]],"date-time":"2021-12-16T10:53:49Z","timestamp":1639652029000},"page":"206-218","update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":52,"title":["AtheroSpectrum Reveals Novel Macrophage Foam Cell Gene Signatures Associated With Atherosclerotic Cardiovascular Disease Risk"],"prefix":"10.1161","volume":"145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9116-450X","authenticated-orcid":true,"given":"Chuan","family":"Li","sequence":"first","affiliation":[{"name":"Department of Immunology (C.L., L.Q., A.J.M., A.T.V., B.Z.), University of Connecticut, Farmington."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5253-6742","authenticated-orcid":true,"given":"Lili","family":"Qu","sequence":"additional","affiliation":[{"name":"Department of Immunology (C.L., L.Q., A.J.M., A.T.V., B.Z.), University of Connecticut, Farmington."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0310-5097","authenticated-orcid":true,"given":"Alyssa J.","family":"Matz","sequence":"additional","affiliation":[{"name":"Department of Immunology (C.L., L.Q., A.J.M., A.T.V., B.Z.), University of Connecticut, Farmington."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2956-1042","authenticated-orcid":true,"given":"Patrick A.","family":"Murphy","sequence":"additional","affiliation":[{"name":"Center for Vascular Biology (P.A.M., A.R.-O.), University of Connecticut, Farmington."},{"name":"Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, MD (P.A.M., W.S.P.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongmei","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Medicine, Divisions of Cardiology and Neurology, Duke University Medical Center, Durham, NC (Y.L.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5998-795X","authenticated-orcid":true,"given":"Ani W.","family":"Manichaikul","sequence":"additional","affiliation":[{"name":"Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville (A.W.M., S.S.R.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9166-8783","authenticated-orcid":true,"given":"Derek","family":"Aguiar","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, University of Connecticut, Storrs (D.A.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3872-7793","authenticated-orcid":true,"given":"Stephen S.","family":"Rich","sequence":"additional","affiliation":[{"name":"Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville (A.W.M., S.S.R.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7670-6400","authenticated-orcid":true,"given":"David M.","family":"Herrington","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC (D.M.H.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Vu","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, University of Washington, Seattle (D.V., W.C.J.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3161-3753","authenticated-orcid":true,"given":"W. 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