Novel proteins associated with risk for coronary heart disease or stroke among postmenopausal women identified by in-depth plasma proteome profiling

Ross L Prentice, Sophie Paczesny, Aaron Aragaki, Lynn M Amon, Lin Chen, Sharon J Pitteri, Martin McIntosh, Pei Wang, Tina Buson Busald, Judith Hsia, Rebecca D Jackson, Jacques E Rossouw, Joann E Manson, Karen Johnson, Charles Eaton, Samir M Hanash, Ross L Prentice, Sophie Paczesny, Aaron Aragaki, Lynn M Amon, Lin Chen, Sharon J Pitteri, Martin McIntosh, Pei Wang, Tina Buson Busald, Judith Hsia, Rebecca D Jackson, Jacques E Rossouw, Joann E Manson, Karen Johnson, Charles Eaton, Samir M Hanash

Abstract

Background: Coronary heart disease (CHD) and stroke were key outcomes in the Women's Health Initiative (WHI) randomized trials of postmenopausal estrogen and estrogen plus progestin therapy. We recently reported a large number of changes in blood protein concentrations in the first year following randomization in these trials using an in-depth quantitative proteomics approach. However, even though many affected proteins are in pathways relevant to the observed clinical effects, the relationships of these proteins to CHD and stroke risk among postmenopausal women remains substantially unknown.

Methods: The same in-depth proteomics platform was applied to plasma samples, obtained at enrollment in the WHI Observational Study, from 800 women who developed CHD and 800 women who developed stroke during cohort follow-up, and from 1-1 matched controls. A plasma pooling strategy, followed by extensive fractionation prior to mass spectrometry, was used to identify proteins related to disease incidence, and the overlap of these proteins with those affected by hormone therapy was examined. Replication studies, using enzyme-linked-immunosorbent assay (ELISA), were carried out in the WHI hormone therapy trial cohorts.

Results: Case versus control concentration differences were suggested for 37 proteins (nominal P < 0.05) for CHD, with three proteins, beta-2 microglobulin (B2M), alpha-1-acid glycoprotein 1 (ORM1), and insulin-like growth factor binding protein acid labile subunit (IGFALS) having a false discovery rate < 0.05. Corresponding numbers for stroke were 47 proteins with nominal P < 0.05, three of which, apolipoprotein A-II precursor (APOA2), peptidyl-prolyl isomerase A (PPIA), and insulin-like growth factor binding protein 4 (IGFBP4), have a false discovery rate < 0.05. Other proteins involved in insulin-like growth factor signaling were also highly ranked. The associations of B2M with CHD (P < 0.001) and IGFBP4 with stroke (P = 0.005) were confirmed using ELISA in replication studies, and changes in these proteins following the initiation of hormone therapy use were shown to have potential to help explain hormone therapy effects on those diseases.

Conclusions: In-depth proteomic discovery analysis of prediagnostic plasma samples identified B2M and IGFBP4 as risk markers for CHD and stroke respectively, and provided a number of candidate markers of disease risk and candidate mediators of hormone therapy effects on CHD and stroke.

Clinical trials registration: ClinicalTrials.gov identifier: NCT00000611.

Figures

Figure 1
Figure 1
Identification and quantitative analysis of peptides in plasma. From CHD cases and controls in eight experiments for (a) beta-2 microglobulin (B2M) and (b) alpha-1-acid glycoprotein 1 (ORM1); and from stroke cases and controls in eight experiments for (c) peptidyl-prolyl isomerase A (PPIA) and (d) insulin-like growth factor binding protein 4 (IGFBP4). Tryptic peptides from the amino terminus (1) to the carboxyl terminus are shown at the top. S, C and G indicate signal peptide, cysteine-containing and glycosylated peptides, respectively. Peptides identified, but which lack cysteine for quantification, are shown in gray. The log2 case/control ratio is shown for cysteine-containing peptides with the number of MS events for that peptide shown in parentheses. The number of plasma fractions where each peptide was quantified is indicated.
Figure 2
Figure 2
Glycolysis/gluconeogenesis pathway. Enzymes identified in stroke experiments are indicated by shading. Red and yellow indicate increased and no change in cases compared to controls, respectively. Gray indicates proteins identified but not quantified.
Figure 3
Figure 3
Baseline plasma B2M concentrations for CHD cases and controls, and IGFBP4 concentrations for stroke cases and controls, from the Women's Health Initiative hormone therapy trials. Individual ELISA-based concentrations are shown along with boxplots showing the median (dark line) and the 25th and 75th percentiles (bottom and top of box). The notches indicate 95% confidence intervals for the median.

References

    1. Women's Health Initiative Steering Committee. Effects of conjugated equine estrogen in postmenopausal women with hysterectomy: the Women's Health Initiative randomized controlled trial. JAMA. 2004;291:1701–1712. doi: 10.1001/jama.291.14.1701.
    1. Writing Group for the Women's Health Initiative Investigators. Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results from the Women's Health Initiative randomized controlled trial. JAMA. 2002;288:321–333. doi: 10.1001/jama.288.3.321.
    1. Hendrix SL, Wassertheil-Smoller S, Johnson KC, Howard BV, Kooperberg C, Rossouw JE, Trevisan M, Aragaki A, Baird AE, Bray PF, Buring JE, Criqui MH, Herrington D, Lynch JK, Rapp SR, Torner J. for the WHI Investigators. Effects of conjugated equine estrogen on stroke in the Women's Health Initiative. Circulation. 2006;113:2425–2434. doi: 10.1161/CIRCULATIONAHA.105.594077.
    1. Wassertheil-Smoller S, Hendrix SL, Limacher M, Heiss G, Kooperberg C, Baird A, Kotchen T, Curb JD, Black H, Rossouw JE, Aragaki A, Safford M, Stein E, Laowattana S, Mysiw WJ. for the WHI Investigators. Effect of estrogen plus progestin on stroke in postmenopausal women: the Women's Health Initiative: a randomized trial. JAMA. 2003;289:2673–2684. doi: 10.1001/jama.289.20.2673.
    1. Hsia J, Langer RD, Manson JE, Kuller L, Johnson KC, Hendrix SL, Pettinger M, Heckbert SR, Greep N, Crawford S, Eaton CB, Kostis JB, Caralis P, Prentice R. for the Women's Health Initiative Investigators. Conjugated equine estrogens and coronary heart disease: the Women's Health Initiative. Arch Intern Med. 2006;166:357–365. doi: 10.1001/archinte.166.3.357.
    1. Manson JE, Hsia J, Johnson KC, Rossouw JE, Assaf AR, Lasser NL, Trevisan M, Black HR, Heckbert SR, Detrano R, Strickland OL, Wong ND, Crouse JR, Stein E, Cushman M. for the Women's Health Initiative Investigators. Estrogen plus progestin and the risk of coronary heart disease. N Engl J Med. 2003;349:523–534. doi: 10.1056/NEJMoa030808.
    1. Chlebowski RT, Hendrix SL, Langer RD, Stefanick ML, Gass M, Lane D, Rodabough RJ, Gilligan MA, Cyr MG, Thomson CA, Khandekar J, Petrovitch H, McTiernan A. for the WHI Investigators. Influence of estrogen plus progestin on breast cancer and mammography in healthy postmenopausal women: the Women's Health Initiative Randomized Trial. JAMA. 2003;289:3243–3253. doi: 10.1001/jama.289.24.3243.
    1. Stefanick ML, Anderson GL, Margolis KL, Hendrix SL, Rodabough RJ, Paskett ED, Lane DS, Hubbell FA, Assaf AR, Sarto GE, Schenken RS, Yasmeen S, Lessin L, Chlebowski RT. for the WHI Investigators. Effects of conjugated equine estrogens on breast cancer and mammography screening in postmenopausal women with hysterectomy. JAMA. 2006;295:1647–1657. doi: 10.1001/jama.295.14.1647.
    1. Katayama H, Paczesny S, Prentice R, Aragaki A, Faca VM, Pitteri SJ, Zhang Q, Wang H, Silva M, Kennedy J, Rossouw J, Jackson R, Hsia J, Chlebowski R, Manson JE, Hanash SM. Application of serum proteomics to the Women's Health Initiative conjugated equine estrogens trial reveals a multitude of effects relevant to clinical findings. Genome Med. 2009;1:47. doi: 10.1186/gm47.
    1. Pitteri SJ, Hanash SM, Aragaki A, Amon LM, Chen L, Busald Buson T, Paczesny S, Katayama H, Wang H, Johnson MM, Zhang Q, McIntosh M, Wang P, Kooperberg C, Rossouw JE, Jackson R, Manson JE, Hsia J, Liu S, Martin L, Prentice RL. Postmenopausal estrogen and progestin effects on the serum proteome. Genome Med. 2009;1:121. doi: 10.1186/gm121.
    1. Faca V, Coram M, Phanstiel D, Glukhova V, Zhang Q, Fitzgibbon M, McIntosh M, Hanash S. Quantitative analysis of acrylamide labeled serum proteins by LC-MS/MS. J Proteome Res. 2006;5:2009–2018. doi: 10.1021/pr060102+.
    1. Faca V, Pitteri SJ, Newcomb L, Glukhova V, Phanstiel D, Krasnoselsky A, Zhang Q, Struthers J, Wang H, Eng J, Fitzgibbon M, McIntosh M, Hanash S. Contribution of protein fractionation to depth of analysis of the serum and plasma proteomes. J Proteome Res. 2007;6:3558–3565. doi: 10.1021/pr070233q.
    1. Faca VM, Song KS, Wang H, Zhang Q, Krasnoselsky AL, Newcomb LF, Plentz RR, Gurumurthy S, Redston MS, Pitteri SJ, Pereira-Faca SR, Ireton RC, Katayama H, Glukhova V, Phanstiel D, Brenner DE, Anderson MA, Misek D, Scholler N, Urban ND, Barnett MJ, Edelstein C, Goodman GE, Thornquist MD, McIntosh MW, DePinho RA, Bardeesy N, Hanash SM. A mouse to human search for plasma proteome changes associated with pancreatic tumor development. PLoS Med. 2008;5:e123. doi: 10.1371/journal.pmed.0050123.
    1. Hanash SM, Pitteri SJ, Faca VM. Mining the plasma proteome for cancer biomarkers. Nature. 2008;452:571–579. doi: 10.1038/nature06916.
    1. The Women's Health Initiative Study Group. Design of the Women's Health Initiative clinical trial and observational study. Control Clin Trials. 1998;19:61–109. doi: 10.1016/S0197-2456(97)00078-0.
    1. Langer RD, White E, Lewis CE, Kotchen JM, Hendrix SL, Trevisan M. The Women's Health Initiative observational study: baseline characteristics of participants and reliability of baseline measures. Ann Epidemiol. 2003;13(9 Suppl):S107–121. doi: 10.1016/S1047-2797(03)00047-4.
    1. Curb JD, McTiernan A, Heckbert SR, Kooperberg C, Stanford J, Nevitt M, Johnson KC, Proulx-Burns L, Pastore L, Criqui M, Daugherty S. WHI Morbidity and Mortality Committee. Outcomes ascertainment and adjudication methods in the Women's Health Initiative. Ann Epidemiol. 2003;13(9 Suppl):S122–128. doi: 10.1016/S1047-2797(03)00048-6.
    1. Rauch A, Bellew M, Eng J, Fitzgibbon M, Holzman T, Hussey P, Igra M, Maclean B, Lin CW, Detter A, Fang R, Faca V, Gafken P, Zhang H, Whiteaker J, States D, Hanash S, Paulovich A, McIntosh MW. Computational Proteomics Analysis System (CPAS): an extensible, open-source analytic system for evaluating and publishing proteomic data and high throughput biological experiments. J Proteome Res. 2006;5:112–121. doi: 10.1021/pr0503533.
    1. Keller A, Nesvizhskii AI, Kolker E, Aebersold R. Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Anal Chem. 2002;74:5383–5392. doi: 10.1021/ac025747h.
    1. Nesvizhskii AI, Keller A, Kolker E, Aebersold R. A statistical model for identifying proteins by tandem mass spectrometry. Anal Chem. 2003;75:4646–4658. doi: 10.1021/ac0341261.
    1. Smyth GK. Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol. 2004;3 Article3.
    1. Smyth GK. In: Bioinformatics and Computational Biology Solutions using R and Bioconductor. Gentleman R, Carey V, Dudoit S, Irizarry R, Huber W, editor. New York: Springer; 2005. Limma: linear models for microarray data. pp. 397–420. full_text.
    1. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Roy Stat Soc B (Methodological) 1995;57:289–300.
    1. Kanehisa M. The KEGG database. Novartis Found Symp. 2002;247:91–101. discussion 101-103, 119-128, 244-252. full_text.
    1. The KEGG PATHWAY Database.
    1. Gorevic PD, Casey TT, Stone WJ, DiRaimondo CR, Prelli FC, Frangione B. Beta-2 microglobulin is an amyloidogenic protein in man. J Clin Invest. 1985;76:2425–2429. doi: 10.1172/JCI112257.
    1. Polat H, Yeksan M, Dalmaz M, Kaptanoglu B, Koşar A, Akkuş I. Serum amyloid A protein levels in haemodialysis patients. Nephrol Dial Transplant. 1996;11:1492–1493.
    1. Saijo Y, Utsugi M, Yoshioka E, Horikawa N, Sato T, Gong Y, Kishi R. Relationship of B2-Microglobulin to arterial stiffness in Japanese subjects. Hypertens Res. 2005;28:505–511. doi: 10.1291/hypres.28.505.
    1. Wilson AM, Kimura E, Harada RK, Nair N, Narasimhan B, Meng X-Y, Zhang F, Beck KR, Olin JW, Fung ET, Cooke JP. B2-Microglobulin as a biomarker in peripheral arterial disease: proteomic profiling and clinical studies. Circulation. 2007;116:1396–1403. doi: 10.1161/CIRCULATIONAHA.106.683722.
    1. Shinkai S, Chaves PHM, Fujiwara Y, Watanabe S, Shibata H, Yoshida H, Suzuki T. B2-Microglobulin for risk stratification of total mortality in the elderly population. Comparison with Cystatin C and C-reactive protein. Arch Intern Med. 2008;168:200–206. doi: 10.1001/archinternmed.2007.64.
    1. Stoppini M, Mangione P, Monti M, Giorgetti S, Marchese L, Arcidiaco P, Verga L, Segagni S, Pucci P, Merlini G, Bellotti V. Proteomics of beta2-microglobulin amyloid fibrils. Biochim Biophys Acta. 2005;1753:23–33.
    1. Johnsen SP, Hundborg HH, Sørensen HT, Orskov H, Tjønneland A, Overvad K, Jørgensen JO. Insulin-like growth factor (IGF) I, -II, and IGF binding protein-3 and risk of ischemic stroke. J Clin Endocrinol Metab. 2005;90:5937–5941. doi: 10.1210/jc.2004-2088.
    1. Denti L, Annoni V, Cattadori E, Salvagnini MA, Visioli S, Merli MF, Corradi F, Ceresini G, Valenti G, Hoffman AR, Ceda GP. Insulin-like growth factor 1 as a predictor of ischemic stroke outcome in the elderly. Am J Med. 2004;117:312–317. doi: 10.1016/j.amjmed.2004.02.049.
    1. Bondanelli M, Ambrosio MR, Onofri A, Bergonzoni A, Lavezzi S, Zatelli MC, Valle D, Basaglia N, degli Uberti EC. Predictive value of circulating insulin-like growth factor I levels in ischemic stroke outcome. J Clin Endocrinol Metab. 2006;91:3928–3934. doi: 10.1210/jc.2006-1040.
    1. Kooijman R, Sarre S, Michotte Y, De Keyser J. Insulin-like growth factor I: a potential neuroprotective compound for the treatment of acute ischemic stroke? Stroke. 2009;40:e83–e88. doi: 10.1161/STROKEAHA.108.528356.
    1. Fournier T, Medjoubi-N N, Porquet D. Alpha-1-acid glycoprotein. Biochim Biophys Acta. 2000;1482:157–171.
    1. Giardina EG, Raby K, Freilich D, Vita J, Brem R, Louie M. Time course of alpha-1-acid glycoprotein and its relation to myocardial enzymes after acute myocardial infarction. Am J Cardiol. 1985;56:262–265. doi: 10.1016/0002-9149(85)90846-X.
    1. Mori T, Sasaki J, Kawaguchi H, Handa K, Takada Y, Matsunaga A, Kono S, Arakawa K. Serum glycoproteins and severity of coronary atherosclerosis. Am Heart J. 1995;129:234–238. doi: 10.1016/0002-8703(95)90003-9.
    1. Held C, Hjemdahl P, Håkan Wallén N, Björkander I, Forslund L, Wiman B, Rehnqvist N. Inflammatory and hemostatic markers in relation to cardiovascular prognosis in patients with stable angina pectoris. Results from the APSIS study. The Angina Prognosis Study in Stockholm. Atherosclerosis. 2000;148:179–188. doi: 10.1016/S0021-9150(99)00240-3.
    1. Kuller LH, Tracy RP, Shaten J, Meilahn EN. Relation of C-reactive protein and coronary heart disease in the MRFIT nested case-control study. Multiple Risk Factor Intervention Trial. Am J Epidemiol. 1996;144:537–547.
    1. Birjmohun RS, Dallinga-Thie GM, Kuivenhoven JA, Stroes ES, Otvos JD, Wareham NJ, Luben R, Kastelein JJ, Khaw KT, Boekholdt SM. Apolipoprotein A-II is inversely associated with risk of future coronary artery disease. Circulation. 2007;116:2029–2035. doi: 10.1161/CIRCULATIONAHA.107.704031.
    1. Matsuda M, Miyahara T, Murai A, Fujimoto N, Kameyama M. Lipoprotein abnormalities in survivors of cerebral infarction with a special reference to apolipoproteins and triglyceride-rich lipoproteins. Atherosclerosis. 1987;68:131–136. doi: 10.1016/0021-9150(87)90103-1.
    1. Walldius G, Aastveit AH, Jungner I. Stroke mortality and the apoB/apoA-I ratio: results of the AMORIS prospective study. J Intern Med. 2006;259:259–266. doi: 10.1111/j.1365-2796.2005.01610.x.
    1. Satoh K, Nigro P, Matoba T, O'Dell MR, Cui Z, Shi X, Mohan A, Yan C, Abe J, Illig KA, Berk BC. Cyclophilin A enhances vascular oxidative stress and the development of angiotensin II-induced aortic aneurysms. Nat Med. 2009;15:649–656. doi: 10.1038/nm.1958.
    1. Colao A. The GH-IGF-I axis and the cardiovascular system: clinical implications. Clin Endocrinol (Oxf) 2008;69:347–358. doi: 10.1111/j.1365-2265.2008.03292.x.
    1. Sandhu MS. Insulin-like growth factor-I and risk of type 2 diabetes and coronary heart disease: molecular epidemiology. Endocr Dev. 2005;9:44–54. full_text.
    1. Boisclair YR, Rhoads RP, Ueki I, Wang J, Ooi GT. The acid-labile subunit (ALS) of the 150 kDa IGF-binding protein complex: an important but forgotten component of the circulating IGF system. J Endocrinol. 2001;170:63–70. doi: 10.1677/joe.0.1700063.
    1. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 2000;25:25–29. doi: 10.1038/75556.
    1. The Women's Health Initiative.

Source: PubMed

3
Suscribir