- Shepherd J.
- Blauw G.J.
- Murphy M.B.
- Bollen E.L.E.M.
- Buckley B.M.
- Cobbe S.M.
- Ford I.
- Gaw A.
- Hyland M.
- Jukema J.W.
- Kamper A.M.
- Macfarlane P.W.
- Meinders A.E.
- Norrie J.
- Packard C.J.
- Perry I.J.
- Stott D.J.
- Sweeney B.J.
- Twomey C.
- Westendorp R.G.J.
Pravastatin in elderly individuals at risk of vascular disease (PROSPER): a randomised controlled trial.
Materials and Methods
Study Population
CAD Severity
Sample Collection and Processing
Quantification of Circulating Markers of Inflammation
- Schuck R.N.
- Theken K.N.
- Edin M.L.
- Caughey M.
- Bass A.
- Ellis K.
- Tran B.
- Steele S.
- Simmons B.P.
- Lih F.B.
- Tomer K.B.
- Wu M.C.
- Hinderliter A.L.
- Stouffer G.A.
- Zeldin D.C.
- Lee C.R.
- Schuck R.N.
- Theken K.N.
- Edin M.L.
- Caughey M.
- Bass A.
- Ellis K.
- Tran B.
- Steele S.
- Simmons B.P.
- Lih F.B.
- Tomer K.B.
- Wu M.C.
- Hinderliter A.L.
- Stouffer G.A.
- Zeldin D.C.
- Lee C.R.
Gene Chip Analysis
eQTL Analysis
R Core Team (2013). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Available at http://www.R-project.org
Overlap of Two Groups of Genes
- Elashoff M.R.
- Wingrove J.A.
- Beineke P.
- Daniels S.E.
- Tingley W.G.
- Rosenberg S.
- Voros S.
- Kraus W.E.
- Ginsburg G.S.
- Schwartz R.S.
- Ellis S.G.
- Tahirkheli N.
- Waksman R.
- McPherson J.
- Lansky A.J.
- Topol E.J.
- Rosenberg S.
- Elashoff M.R.
- Beineke P.
- Daniels S.E.
- Wingrove J.A.
- Tingley W.G.
- Sager P.T.
- Sehnert A.J.
- Yau M.
- Kraus W.E.
- Newby L.K.
- Schwartz R.S.
- Voros S.
- Ellis S.G.
- Tahirkheli N.
- Waksman R.
- McPherson J.
- Lansky A.
- Winn M.E.
- Schork N.J.
- Topol E.J.
Results
Study Population
Characteristic | Obstructive CAD (n = 93) | No obstructive CAD (n = 50) | P value |
---|---|---|---|
Age, years | 74 ± 6.3 | 73 ± 6.2 | 0.220 |
Male sex | 57 (61) | 18 (36) | 0.004 |
White race | 74 (80) | 37 (74) | 0.446 |
Body mass index, kg/m2 | 29 ± 6.3 | 30 ± 7.1 | 0.323 |
Current smoker | 4 (4) | 3 (6) | 0.653 |
Diabetes | 38 (41) | 17 (34) | 0.421 |
Hyperlipidemia | 74 (80) | 28 (56) | 0.003 |
Hypertension | 82 (88) | 44 (88) | 0.976 |
Previous MI | 41 (44) | 3 (6) | <0.001 |
Multivessel disease | 62 (67) | 0 (0) | <0.001 |
Systolic blood pressure, mmHg | 143 ± 20 | 141 ± 20 | 0.573 |
Diastolic blood pressure, mmHg | 77 ± 13 | 78 ± 12 | 0.588 |
Statin use | 74 (80) | 23 (46) | <0.001 |
Aspirin use | 78 (84) | 33 (66) | 0.015 |
Clopidogrel use | 33 (36) | 6 (12) | 0.003 |
Circulating Biomarkers of Inflammation
The Protective Chemokine CXCL5 Inversely Correlates with CAD Severity

Analyte | P value | OR (95% CI) | Reciprocal OR | CAD Class 0–4 | |
---|---|---|---|---|---|
Ordinal | |||||
CXCL5 unit odds | 0.0013 | 0.52 (0.36–0.78) | 1.91 | 1570, 1638, 1048, 1324, 886 | |
Adjusted model | |||||
CXCL5 unit odds adj | 0.0148 | 0.59 (0.39–0.90) | 1.69 | ||
Prior statin use (Y) adj | 0.0023 | 1.75 (1.15–2.67) | 5%, 19%, 25%, 21%, 31% | ||
Sex (M) adj | 0.0003 | 1.78 (1.27–2.48) | 7%, 17%, 18%, 24%, 33% | ||
Analyte | P | OR (95% CI) | Recip | Obstructive CAD-no | Obstructive CAD-yes |
Nominal | |||||
CXCL5 unit odds | 0.0014 | 0.46 (0.27–0.75) | 2.15 | 1638 (1439) | 998 (943) |
CXCL5 range odds | 0.03 (3.2E-3–0.30) | 32.06 | |||
Adjusted model | |||||
CXCL5 unit odds adj | 0.0309 | 0.54 (0.31–0.96) | 1.84 | ||
CXCL5 range odds adj | 0.06 (4.7E-3 - 0.84) | 57.33 | |||
Prior statin usage (Y) adj | 0.0100 | 4.02 (1.39–11.58) | 46% | 80% | |
Sex (M) adj | 0.0140 | 3.03 (1.25–7.33) | 36% | 61% |


hsCRP, but Not Other Circulating Inflammatory Biomarkers, Correlates with CAD Severity
- Ridker P.M.
- Cannon C.P.
- Morrow D.
- Rifai N.
- Rose L.M.
- McCabe C.H.
- Pfeffer M.A.
- Braunwald E.
C-reactive protein levels and outcomes after statin therapy.
- Chang T.-Y.
- Hsu C.-Y.
- Huang P.-H.
- Chiang C.-H.
- Leu H.-B.
- Huang C.-C.
- Chen J.-W.
- Lin S.-J.
- Peer A.
- Falkensammer G.
- Alber H.
- Kroiss A.
- Griesmacher A.
- Ulmer H.
- Pachinger O.
- Mair J.
Analyte | P value | OR (95% CI) | CAD Class 0–4 | |
---|---|---|---|---|
Ordinal | ||||
MCP1 | 0.706 | 0.90 (0.51–1.59) | 106, 125, 132, 127, 109 | |
MCP1 adj | 0.586 | 0.99 (0.54–1.84) | ||
hsCRP | 0.105 | 1.04 (0.99–1.09) | 4.9, 4.4, 4.3, 5.8, 8.1 | |
hsCRP adj | 0.021 | 1.06 (1.01–1.12) | ||
hsCRPmed [1] | 0.137 | 1.55 (0.87–2.80) | 11%, 20%, 18%, 21%, 30% [1] | |
hsCRPmed adj [1] | 0.097 | 1.68 (1.59–1.76) | 14%, 25%, 25%, 15%, 21% [0] | |
CAM score | 0.285 | 1.08 (0.94–1.23) | −0.12, −0.07, −0.044, 0.60, −0.16 | |
CAM score adj | 0.548 | 1.04 (0.91–1.20) | ||
Analyte | P | OR (95% CI) | Obstructive CAD-no | Obstructive CAD-yes |
Nominal | ||||
MCP1 unit | 0.661 | 1.16 (0.59–2.29) | 115 (46) | 122 (58) |
MCP1 range | 1.77 (0.14–22.5) | |||
MCP1 unit adj | 0.521 | 1.30 (0.59–2.87) | ||
MCP1 range adj | 2.68 (0.13–54.5) | |||
hsCRP unit | 0.212 | 1.04 (0.98–1.10) | 4.6 (13.8) | 5.7 (13.1) |
hsCRP range | 1.72 (0.73–4.04) | |||
hsCRP unit adj | 0.083 | 1.06 (0.99–1.14) | ||
hsCRP range adj | 2.41 (0.88–6.63) | |||
hsCRPmed [1] | 0.321 | 1.42 (0.71–2.85) | 15%/20% [1/0] | 34%/31% [1/0] |
hsCRPmed adj [1] | 0.201 | 1.69 (0.75–3.80) | ||
CAM score unit | 0.485 | 1.06 (0.90–1.25) | −0.07 (2.86) | 0.10 (2.68) |
CAM score range | 1.92 (0.90–1.25) | |||
CAM score unit adj | 0.665 | 1.04 (0.87–1.25) | ||
CAM score range adj | 1.58 (0.20–12.6) |
Global Gene Expression and Genotype Profiling
Polymorphisms Associated with CXCL5 Expression and Circulating CXCL5 Levels

- Zeller T.
- Wild P.
- Szymczak S.
- Rotival M.
- Schillert A.
- Castagne R.
- Maouche S.
- Germain M.
- Lackner K.
- Rossmann H.
- Eleftheriadis M.
- Sinning C.R.
- Schnabel R.B.
- Lubos E.
- Mennerich D.
- Rust W.
- Perret C.
- Proust C.
- Nicaud V.
- Loscalzo J.
- Hübner N.
- Tregouet D.
- Münzel T.
- Ziegler A.
- Tiret L.
- Blankenberg S.
- Cambien F.
- Zeller T.
- Wild P.
- Szymczak S.
- Rotival M.
- Schillert A.
- Castagne R.
- Maouche S.
- Germain M.
- Lackner K.
- Rossmann H.
- Eleftheriadis M.
- Sinning C.R.
- Schnabel R.B.
- Lubos E.
- Mennerich D.
- Rust W.
- Perret C.
- Proust C.
- Nicaud V.
- Loscalzo J.
- Hübner N.
- Tregouet D.
- Münzel T.
- Ziegler A.
- Tiret L.
- Blankenberg S.
- Cambien F.
- Kirsten H.
- Al-Hasani H.
- Holdt L.
- Gross A.
- Beutner F.
- Krohn K.
- Horn K.
- Ahnert P.
- Burkhardt R.
- Reiche K.
- Hackermüller J.
- Löffler M.
- Teupser D.
- Thiery J.
- Scholz M.
CXCL5 Polymorphisms Associated with CAD in a Larger Cohort

Cohort | Participants, n | P value | OR (95% CI) | Reciprocal OR |
---|---|---|---|---|
SAMARA 1 | 116 | 0.0612 | 0.48 (0.22–1.05) | 2.15 |
SAMARA 2 | 106 | 0.0330 | 0.40 (0.17–0.93) | 2.51 |
SAMARA 1 and 2 | 222 | 0.0037 | 0.43 (0.24–0.77) | 2.31 |
Identifying Molecular Phenotypes of CXCL5-Related CAD in a Geriatric Cohort
- Elashoff M.R.
- Wingrove J.A.
- Beineke P.
- Daniels S.E.
- Tingley W.G.
- Rosenberg S.
- Voros S.
- Kraus W.E.
- Ginsburg G.S.
- Schwartz R.S.
- Ellis S.G.
- Tahirkheli N.
- Waksman R.
- McPherson J.
- Lansky A.J.
- Topol E.J.
- Rosenberg S.
- Elashoff M.R.
- Beineke P.
- Daniels S.E.
- Wingrove J.A.
- Tingley W.G.
- Sager P.T.
- Sehnert A.J.
- Yau M.
- Kraus W.E.
- Newby L.K.
- Schwartz R.S.
- Voros S.
- Ellis S.G.
- Tahirkheli N.
- Waksman R.
- McPherson J.
- Lansky A.
- Winn M.E.
- Schork N.J.
- Topol E.J.
- Kirsten H.
- Al-Hasani H.
- Holdt L.
- Gross A.
- Beutner F.
- Krohn K.
- Horn K.
- Ahnert P.
- Burkhardt R.
- Reiche K.
- Hackermüller J.
- Löffler M.
- Teupser D.
- Thiery J.
- Scholz M.
- Fehrmann R.S.N.
- Jansen R.C.
- Veldink J.H.
- Westra H.-J.
- Arends D.
- Bonder M.J.
- Fu J.
- Deelen P.
- Groen H.J.M.
- Smolonska A.
- Weersma R.K.
- Hofstra R.M.W.
- Buurman W.A.
- Rensen S.
- Wolfs M.G.M.
- Platteel M.
- Zhernakova A.
- Elbers C.C.
- Festen E.M.
- Trynka G.
- Hofker M.H.
- Saris C.G.J.
- Ophoff R.A.
- van den Berg L.H.
- van Heel D.A.
- Wijmenga C.
- te Meerman G.J.
- Franke L.
Comparison | Set 1 | Set 2 | Overlap | Total | Representation factor | P value |
---|---|---|---|---|---|---|
SAMARA vs CATHGEN/PREDICT | 618 | 655 | 43 | 29,281 | 3.1 | 6.70 × 10−11 |
CXCL5 vs CAD | 1041 | 681 | 253 | 18,425 | 6.6 | 6.01 × 10−145 |

- Kirsten H.
- Al-Hasani H.
- Holdt L.
- Gross A.
- Beutner F.
- Krohn K.
- Horn K.
- Ahnert P.
- Burkhardt R.
- Reiche K.
- Hackermüller J.
- Löffler M.
- Teupser D.
- Thiery J.
- Scholz M.
rs Identification | Gene symbol | Gene description | P value | FDR, % | β Value |
---|---|---|---|---|---|
rs12708952 | LPCAT2 | Lysophosphatidylcholine acyltransferase 2 | 3 × 10−7 | 0.1 | −0.52 |
rs4402561 | LPCAT2 | Lysophosphatidylcholine acyltransferase 2 | 4 × 10−7 | 0.1 | 0.49 |
rs1891241 | LGALS8 | Lectin, galactoside-binding, soluble, 8 | 2 × 10−6 | 0.4 | −0.33 |
rs1796415 | RNF10 | Ring finger protein 10 | 4 × 10−6 | 0.8 | 0.60 |
rs10158939 | RP11-553N16.1 | Known processed pseudogene | 5 × 10−6 | 0.9 | −0.24 |
rs11254468 | VIM | Vimentin | 7 × 10−6 | 1.3 | 0.43 |
rs6599244 | RPL18AP7 | Ribosomal protein L18a pseudogene 7 | 1 × 10−5 | 1.9 | 0.44 |
rs9511357 | ZMYM5 | Zinc finger, MYM-type 5 | 1 × 10−5 | 2.2 | −0.18 |
rs831757 | ARL8A | ADP-ribosylation factor-like 8A | 2 × 10−5 | 2.5 | −0.23 |
rs2799428 | LGALS8 | Lectin, galactoside-binding, soluble, 8 | 2 × 10−5 | 2.8 | −0.29 |
rs244836 | COTL1 | Coactosin-like F-actin binding protein 1 | 2 × 10−5 | 2.9 | 0.23 |
rs1583585 | LPCAT2 | Lysophosphatidylcholine acyltransferase 2 | 2 × 10−5 | 3.2 | −0.41 |
rs1963773 | RNF10 | Ring finger protein 10 | 2 × 10−5 | 3.4 | −0.45 |
rs41416850 | RNF10 | Ring finger protein 10 | 2 × 10−5 | 3.4 | −0.63 |
rs2737706 | LGALS8 | Lectin, galactoside-binding, soluble, 8 | 3 × 10−5 | 3.7 | 0.30 |
rs1583587 | LPCAT2 | Lysophosphatidylcholine acyltransferase 2 | 3 × 10−5 | 3.9 | 0.42 |
rs3779647 | GSR | Glutathione reductase | 3 × 10−5 | 4.0 | −0.19 |
rs913863 | RRAGC | Ras-related GTP binding C | 4 × 10−5 | 4.8 | −0.10 |
rs11646643 | LPCAT2 | Lysophosphatidylcholine acyltransferase 2 | 5 × 10−05 | 6.0 | −0.41 |
rs9989481 | UBALD2 | UBA-like domain containing 2 | 6 × 10−5 | 6.3 | 0.24 |
rs11206237 | TALDO1 | Transaldolase 1 | 6 × 10−5 | 6.8 | −0.44 |
rs913863 | RRAGC | Ras-related GTP binding C | 7 × 10−5 | 7.3 | −0.10 |
rs1477017 | LPCAT2 | Lysophosphatidylcholine acyltransferase 2 | 7 × 10−5 | 7.6 | 0.40 |
rs1799917 | LPCAT2 | Lysophosphatidylcholine acyltransferase 2 | 7 × 10−5 | 7.6 | 0.41 |
rs2715143 | GRB10 | Growth factor receptor-bound protein 10 | 7 × 10−5 | 7.6 | −0.84 |
rs9553323 | ZMYM5 | Zinc finger, MYM-type 5 | 7 × 10−5 | 7.7 | −0.17 |
rs4415303 | GYG1P1 | Glycogenin 1 pseudogene 1 | 8 × 10−5 | 7.8 | 0.49 |
rs1611699 | HLA-K | Major histocompatibility complex, class I, K | 9 × 10−5 | 8.5 | −0.18 |
rs3013777 | YIPF1 | Yip1 domain family, member 1 | 1 × 10−4 | 9.5 | −0.21 |
rs11185517 | NCBP2-AS2 | NCBP2 antisense RNA 2 (head to head) | 1 × 10−4 | 9.7 | 0.16 |

Discussion
- Hwang S.J.
- Ballantyne C.M.
- Sharrett A.R.
- Smith L.C.
- Davis C.E.
- Gotto A.M.
- Boerwinkle E.
- Folsom A.R.
- Chambless L.E.
- Ballantyne C.M.
- Coresh J.
- Heiss G.
- Wu K.K.
- Boerwinkle E.
- Mosley T.H.
- Sorlie P.
- Diao G.
- Sharrett A.R.
- Rodondi N.
- Marques-Vidal P.
- Butler J.
- Sutton-Tyrrell K.
- Cornuz J.
- Satterfield S.
- Harris T.
- Bauer D.C.
- Ferrucci L.
- Vittinghoff E.
- Newman A.B.
Markers of atherosclerosis and inflammation for prediction of coronary heart disease in older adults.
Acknowledgments
Supplemental Data
- Supplemental Figure S1
Allele frequency of rs394408 in different ancestral populations. The allele frequency of the minor (T) and major (C) alleles represented by a stacked bar plot. For reference, the 5% minor allele frequency (MAF) cutoff is indicated by a green arrow, and frequencies <5% are usually considered rare within a population. Data from the following ancestral populations are provided: Han Chinese in Beijing, China (CHB); Japanese in Tokyo, Japan (JPT); Mexican ancestry in Los Angeles, CA (MXL); British in England and Scotland (GRB); Utah residents with Northern and Western European ancestry (CEU); Puerto Ricans from Puerto Rico (PUR); African ancestry in Southwest United States (ASW); and Yoruba in Ibadan, Nigeria (YRI).
54The expected allele frequency in Supporting a Multidisciplinary Approach to Researching Atherosclerosis (SAMARAex) for rs394408 within the SAMARA cohort (phase 1 and phase 2) was calculated using the corresponding frequencies found in the black (ASW) and white (CEU) American F1000 population data. The observed allele frequency (SAMARAobs) is also provided.
- Supplemental Figure S2
Association of lysophosphatidylcholine acyltransferase 2 (LPCAT2) expression, platelet factor 4 (PF4) expression, and platelet counts. Pairwise association analysis (Pearson) of the indicated variables summarized by scatterplot, regression line, and means (95% CIs). The histogram of the variable distribution is provided. The unit of mRNA is relative expression, and platelets are log transformed. The correlation coefficient for each association is indicated. ∗P < 0.05 LPCAT2 versus platelet counts; ∗∗P < 0.01 LPCAT2 versus PF4.
- Supplemental Table S1
- Supplemental Table S2
- Supplemental Table S3
- Supplemental Table S4
- Supplemental Table S5
- Supplemental Table S6
- Supplemental Table S7
References
- Lifetime risks of cardiovascular disease.N Engl J Med. 2012; 366: 321-329
- Heart disease and stroke statistics–2012 update: a report from the American Heart Association.Circulation. 2012; 125: e2-e220
- Arterial and cardiac aging: major shareholders in cardiovascular disease enterprises, part I: aging arteries: a “set up” for vascular disease.Circulation. 2003; 107: 139-146
- Inflammation, atherosclerosis, and coronary artery disease.N Engl J Med. 2005; 352: 1685-1695
- Inflammation in atherosclerosis.Nature. 2002; 420: 868-874
- Inflammation and atherosclerosis.Circulation. 2002; 105: 1135-1143
- Treatment of hypertension in patients 80 years of age or older.N Engl J Med. 2008; 358: 1887-1898
- Pravastatin in elderly individuals at risk of vascular disease (PROSPER): a randomised controlled trial.Lancet. 2002; 360: 1623-1630
- Gene expression patterns in peripheral blood correlate with the extent of coronary artery disease.PLoS One. 2009; 4: e7037
- Correlation of peripheral-blood gene expression with the extent of coronary artery stenosis.Circ Cardiovasc Genet. 2008; 1: 31-38
- CXCL5 is associated with the increased risk of coronary artery disease.Coron Artery Dis. 2015; 26: 612-619
- Serum CXC ligand 5 is a new marker of subclinical atherosclerosis in type 2 diabetes.Clin Endocrinol (Oxf). 2011; 75: 766-770
- CXCL5 limits macrophage foam cell formation in atherosclerosis.J Clin Invest. 2013; 123: 1343-1347
- Nonobstructive coronary artery disease and risk of myocardial infarction.JAMA. 2014; 312: 1754-1763
- Prevalence and predictors of nonobstructive coronary artery disease identified with coronary angiography in contemporary clinical practice.Am Heart J. 2014; 167 (e2): 846-852
- Tobacco use induces anti-apoptotic, proliferative patterns of gene expression in circulating leukocytes of Caucasian males.BMC Med Genomics. 2008; 1: 38
- Stable patterns of gene expression regulating carbohydrate metabolism determined by geographic ancestry.PLoS One. 2009; 4: e8183
- Cytochrome P450-derived eicosanoids and vascular dysfunction in coronary artery disease patients.Atherosclerosis. 2013; 227: 442-448
- Age as a modulator of inflammatory cardiovascular risk factors.Arterioscler Thromb Vasc Biol. 2011; 31: 2151-2156
- The BioMart community portal: an innovative alternative to large, centralized data repositories.Nucleic Acids Res. 2015; 43: W589-W598
- MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes.Genet Epidemiol. 2010; 34: 816-834
- Matrix eQTL: ultra fast eQTL analysis via large matrix operations.Bioinformatics. 2012; 28: 1353-1358
R Core Team (2013). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Available at http://www.R-project.org
- Development of a blood-based gene expression algorithm for assessment of obstructive coronary artery disease in non-diabetic patients.BMC Med Genomics. 2011; 4: 26
- Multicenter validation of the diagnostic accuracy of a blood-based gene expression test for assessing obstructive coronary artery disease in nondiabetic patients.Ann Intern Med. 2010; 153: 425-434
- A new look at the statistical model identification.IEEE Trans Autom Control. 1974; 19: 716-723
- Molecular sex differences in human serum.PLoS One. 2012; 7: e51504
- Epithelial neutrophil-activating peptide (ENA-78), acute coronary syndrome prognosis, and modulatory effect of statins.PLoS One. 2008; 3: e3117
- Endometrial expression of epithelial neutrophil-activating peptide-78 during the menstrual cycle or in progestin-only contraceptive users with breakthrough bleeding and the influence of doxycycline therapy.Hum Reprod. 2007; 22: 427-433
- Human endothelial cells synthesize ENA-78: relationship to IL-8 and to signaling of PMN adhesion.Am J Respir Cell Mol Biol. 1997; 17: 181-192
- Induction of CXCL5 during inflammation in the rodent lung involves activation of alveolar epithelium.Am J Respir Cell Mol Biol. 2005; 32: 531-539
- Epithelial neutrophil activating peptide-78: a novel chemotactic cytokine for neutrophils in arthritis.J Clin Invest. 1994; 94: 1012-1018
- CXCL1/KC and CXCL5/LIX are selectively produced by corneal fibroblasts and mediate neutrophil infiltration to the corneal stroma in LPS keratitis.J Leukoc Biol. 2007; 81: 786-792
- CXCL5 regulates chemokine scavenging and pulmonary host defense to bacterial infection.Immunity. 2010; 33: 106-117
- Cxcr2 and Cxcl5 regulate the IL-17/G-CSF axis and neutrophil homeostasis in mice.J Clin Invest. 2012; 122: 974-986
- CXCL5 signaling is a shared pathway of neuroinflammation and blood-brain barrier injury contributing to white matter injury in the immature brain.J Neuroinflammation. 2016; 13: 6
- Quantifying effect of statins on low density lipoprotein cholesterol, ischaemic heart disease, and stroke: systematic review and meta-analysis.Vasc Med. 2003; 8: 289-290
- Comparative dose efficacy study of atorvastatin versus simvastatin, pravastatin, lovastatin, and fluvastatin in patients with hypercholesterolemia (the CURVES study).Am J Cardiol. 1998; 81: 582-587
- Comparison of the efficacy and safety of rosuvastatin versus atorvastatin, simvastatin, and pravastatin across doses (STELLAR* Trial).Am J Cardiol. 2003; 92: 152-160
- Circulating cell adhesion molecules and death in patients with coronary artery disease.Circulation. 2001; 104: 1336-1342
- Serial measurement of monocyte chemoattractant protein-1 after acute coronary syndromes: results from the A to Z trial.J Am Coll Cardiol. 2007; 50: 2117-2124
- Inflammation, aspirin, and the risk of cardiovascular disease in apparently healthy men.N Engl J Med. 1997; 336: 973-979
- C-reactive protein levels and outcomes after statin therapy.N Engl J Med. 2005; 352: 20-28
- Should we measure C-reactive protein on Earth or just on JUPITER?.Clin Cardiol. 2010; 33: 190-198
- Rev Port Cardiol. 2012; 31 (Portuguese): 733-745
- Usefulness of circulating decoy receptor 3 in predicting coronary artery disease severity and future major adverse cardiovascular events in patients with multivessel coronary artery disease.Am J Cardiol. 2015; 116: 1028-1033
- Association of C-reactive protein and homocysteine with subclinical coronary plaque subtype and stenosis using low-dose MDCT coronary angiography.Atherosclerosis. 2010; 212: 501-506
- Limited utilities of N-terminal pro B-type natriuretic peptide and other newer risk markers compared with traditional risk factors for prediction of significant angiographic lesions in stable coronary artery disease.Heart. 2009; 95: 297-303
- Treg/Th17 balance in stable CAD patients with different stages of coronary atherosclerosis.Atherosclerosis. 2015; 238: 17-21
- Monocyte-endothelial cell interactions in the development of atherosclerosis.Trends Cardiovasc Med. 2008; 18: 228-232
- CXCL5 polymorphisms are associated with variable blood pressure in cardiovascular disease-free adults.Hum Genomics. 2012; 6: 9
- CXCL5 gene polymorphisms are related to systemic concentrations and leukocyte production of epithelial neutrophil-activating peptide (ENA-78).Cytokine. 2006; 33: 258-263
- Genetics and beyond: the transcriptome of human monocytes and disease susceptibility.PLoS One. 2010; 5: e10693
- A global reference for human genetic variation.Nature. 2015; 526: 68-74
- LDlink: a web-based application for exploring population-specific haplotype structure and linking correlated alleles of possible functional variants.Bioinformatics. 2015; 31: 3555-3557
- Dissecting the genetics of the human transcriptome identifies novel trait-related trans-eQTLs and corroborates the regulatory relevance of non-protein coding loci†.Hum Mol Genet. 2015; 24: 4746-4763
- Circulatory neutrophil chemokines in statin-treated diabetic patients.Saudi Med J. 2008; 29: 584-588
- Elevated serum chemokine CXC ligand 5 levels are associated with hypercholesterolemia but not a worsening of insulin resistance in Chinese people.J Clin Endocrinol Metab. 2010; 95: 3926-3932
- Trans-eQTLs reveal that independent genetic variants associated with a complex phenotype converge on intermediate genes, with a major role for the HLA.PLoS Genet. 2011; 7: e1002197
- Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.Proc Natl Acad Sci U S A. 2005; 102: 15545-15550
- MicroRNAs in the human heart: a clue to fetal gene reprogramming in heart failure.Circulation. 2007; 116: 258-267
- A transcriptional profile of aging in the human kidney.PLoS Biol. 2004; 2: e427
- Immune response in silico (IRIS): immune-specific genes identified from a compendium of microarray expression data.Genes Immun. 2005; 6: 319-331
- Combined deficiency of proapoptotic regulators Bim and Fas results in the early onset of systemic autoimmunity.Immunity. 2008; 28: 206-217
- Gene expression patterns in blood leukocytes discriminate patients with acute infections.Blood. 2007; 109: 2066-2077
- Network analysis reveals centrally connected genes and pathways involved in CD8+ T cell exhaustion versus memory.Immunity. 2012; 37: 1130-1144
- Gene expression profiles during human CD4+ T cell differentiation.Int Immunol. 2004; 16: 1109-1124
- Identification of novel genes regulated by IL-12, IL-4, or TGF-beta during the early polarization of CD4+ lymphocytes.J Immunol. 2003; 171: 5328-5336
- Platelet activating factor in heart failure: potential role in disease progression and novel target for therapy.Curr Heart Fail Rep. 2013; 10: 122-129
- Circulating adhesion molecules VCAM-1, ICAM-1, and E-selectin in carotid atherosclerosis and incident coronary heart disease cases: the Atherosclerosis Risk In Communities (ARIC) study.Circulation. 1997; 96: 4219-4225
- An assessment of incremental coronary risk prediction using C-reactive protein and other novel risk markers: the Atherosclerosis Risk in Communities Study.Arch Intern Med. 2006; 166: 1368-1373
- Comparison of C-reactive protein and low-density lipoprotein cholesterol levels in the prediction of first cardiovascular events.N Engl J Med. 2002; 347: 1557-1565
- Markers of atherosclerosis and inflammation for prediction of coronary heart disease in older adults.Am J Epidemiol. 2010; 171: 540-549
- Challenges in the phenotypic characterisation of patients in genetic studies of coronary artery disease.J Med Genet. 2007; 44: 161-165
Article Info
Publication History
Footnotes
Supported by a Le Fondation Leducq Trans-Atlantic Network of Excellence grant, The University of North Carolina at Chapel Hill grant 6066230 (Investments in the Future: Understanding Clinical Cardiovascular Disease and Health Disparities in North Carolina Using a Systems Biology Approach), American Heart Association grant 16GRNT29300003 (C.R.L.) and predoctoral fellowship 11PRE7240059 (R.N.S.), NIH/National Heart, Lung, and Blood Institute (NHLBI) predoctoral training program in Integrative Vascular Biology T32 HL069768 , and NIH/NHLBI grant 4R37HL065619 (C.P.). The Genotype-Tissue Expression Project was supported by the Common Fund of the Office of the Director of the NIH and by National Cancer Institute, National Human Genome Research Institute, NHLBI, National Institute of Drug Abuse, National Institute of Mental Health, and National Institute of Neurological Diseases and Stroke.
Disclosures: None declared.
Identification
Copyright
User License
Elsevier user license |
Permitted
For non-commercial purposes:
- Read, print & download
- Text & data mine
- Translate the article
Not Permitted
- Reuse portions or extracts from the article in other works
- Redistribute or republish the final article
- Sell or re-use for commercial purposes
Elsevier's open access license policy