C-reactive protein, a conserved acute-phase protein synthesized in the liver and involved in inflammation, infection, and tissue damage, is an informative biomarker for human cardiovascular disease. Out of 258 captive adult common chimpanzees (Pan troglodytes) assayed for CRP, 27.9% of the data were below the quantitation limit. Data were analyzed by the Kaplan-Meier method and results compared to other methods for handling censored data (including deletion, replacement, and imputation). Kaplan-Meier results demonstrated a modest age effect and a strong effect of HCV infection in reducing CRP but did not allow inference of reference intervals. Results of other methods varied considerably. Substitution schemes differed widely in statistical significance, with estimated group means biased by the size of the substitution constant, while inference of unbiased reference intervals was impossible. Single imputation gave reasonable statistical inferences but unreliable reference intervals. Multiple imputation gave reliable results, for both statistical inference and reference intervals, and was comparable to the Kaplan-Meier standard. Other methods should be avoided. CRP did not predict cardiovascular disease, but CRP levels were reduced by 50% in animals with hepatitis C infection and showed inverse relationships with 2 liver function enzymes. Results suggested that hsCRP can be an informative biomarker of chronic hepatic dysfunction. 1. Introduction C-reactive protein (CRP), a phylogenetically highly conserved protein, has become an important biomarker of acute inflammation and tissue damage in humans [1–3]. CRP is an important biomarker for many aspects of health and disease, including cardiovascular disease, type 2 diabetes, and chronic renal disease and is a predictor of all-cause mortality [2, 4–7]. CRP is synthesized by hepatocytes when induced by cytokines including IL-6 [1, 4]. Circulating plasma levels can rise during the acute-phase response to inflammation, infection, or trauma by 10,000-fold and decrease just as rapidly [1, 2, 8]. CRP has many biological functions related to the recognition and clearance of foreign pathogens and damaged host cells, binding chromatin and small nuclear ribonucleoproteins, which suggested a role in clearance of debris due to apoptosis and necrosis [2, 4, 8]. CRP stimulates the classical complement pathway [1, 2, 4]. Its activation by the same Fc receptors used by IgG, and its earlier response to infection, suggested a role in inducing an adaptive immune response [4]. CRP is also involved in the development of
References
[1]
S. Black, I. Kushner, and D. Samols, “C-reactive protein,” Journal of Biological Chemistry, vol. 279, no. 47, pp. 48487–48490, 2004.
[2]
G. M. Hirschfield and M. B. Pepys, “C-reactive protein and cardiovascular disease: new insights from an old molecule,” Monthly Journal of the Association of Physicians, vol. 96, no. 11, pp. 793–807, 2003.
[3]
T. B. Ledue and N. Rifai, “Preanalytic and analytic sources of variations in C-reactive protein measurement: Implications for cardiovascular disease risk assessment,” Clinical Chemistry, vol. 49, no. 8, pp. 1258–1271, 2003.
[4]
T. W. Du Clos, “Function of C-reactive protein,” Annals of Medicine, vol. 32, no. 4, pp. 274–278, 2000.
[5]
M. Hamer, Y. Chida, and E. Stamatakis, “Association of very highly elevated C-reactive protein concentration with cardiovascular events and all-cause mortality,” Clinical Chemistry, vol. 56, no. 1, pp. 132–135, 2010.
[6]
A. D. Pradhan, J. E. Manson, N. Rifai, J. E. Buring, and P. M. Ridker, “C-reactive protein, interleukin 6, and risk of developing type 2 diabetes mellitus,” Journal of the American Medical Association, vol. 286, no. 3, pp. 327–334, 2001.
[7]
J. Zacho, A. Tybj？rg-Hansen, and B. G. Nordestgaard, “C-reactive protein and all-cause mortality-the Copenhagen City Heart Study,” European Heart Journal, vol. 31, no. 13, pp. 1624–1632, 2010.
R. Ross, “Atherosclerosis-an inflammatory disease,” The New England Journal of Medicine, vol. 340, pp. 115–126, 1999.
[10]
A. R. Folsom, L. E. Chambless, C. M. Ballantyne et al., “An assessment of incremental coronary risk prediction using C-reactive protein and other novel risk markers: the atherosclerosis risk in communities study,” Archives of Internal Medicine, vol. 166, no. 13, pp. 1368–1373, 2006.
[11]
T. A. Pearson, G. A. Mensah, R. W. Alexander et al., “Markers of inflammation and cardiovascular disease: application to clinical and public health practice: a statement for healthcare professionals from the centers for disease control and prevention and the American Heart Association,” Circulation, vol. 107, no. 3, pp. 499–511, 2003.
[12]
P. M. Ridker, M. Cushman, M. J. Stampfer, R. P. Tracy, and C. H. Hennekens, “Plasma concentration of C-reactive protein and risk of developing peripheral vascular disease,” Circulation, vol. 97, no. 5, pp. 425–428, 1998.
[13]
S. Mora, K. Musunuru, and R. S. Blumenthal, “The clinical utility of high-sensitivity C-reactive protein in cardiovascular disease and the potential implication of JUPITER on current practice guidelines,” Clinical Chemistry, vol. 55, no. 2, pp. 219–228, 2009.
[14]
P. M. Ridker, N. Rifai, L. Rose, J. E. Buring, and N. R. Cook, “Comparison of C-reactive protein and low-density lipoprotein cholesterol levels in the prediction of first cardiovascular events,” The New England Journal of Medicine, vol. 347, no. 20, pp. 1557–1565, 2002.
[15]
P. M. Ridker, J. E. Buring, N. R. Cook, and N. Rifai, “C-reactive protein, the metabolic syndrome, and risk of incident cardiovascular events: an 8-year follow-up of 14 719 initially healthy American women.,” Circulation, vol. 107, no. 3, pp. 391–397, 2003.
[16]
J. Danesh, R. Collins, P. Appleby, and R. Peto, “Association of fibrinogen, C-reactive protein, albumin, or leukocyte count with coronary heart disease: meta-analyses of prospective studies,” Journal of the American Medical Association, vol. 279, no. 18, pp. 1477–1482, 1998.
[17]
J. Danesh, P. Whincup, W. Walker, et al., “Low grade inflammation and coronary heart disease: prospective study and updated meta-analyses,” British Medical Journal, vol. 321, pp. 199–204, 2000.
[18]
W. Koenig, N. Khuseyinova, J. Baumert, and C. Meisinger, “Prospective study of high-sensitivity C-reactive protein as a determinant of mortality: results from the MONICA/KORA Augsburg cohort study, 1984–1998,” Clinical Chemistry, vol. 54, no. 2, pp. 335–342, 2008.
[19]
J. J. Ely, M. A. Bishop, M. L. Lammey, M. M. Sleeper, J. M. Steiner, and D. R. Lee, “Use of biomarkers of collagen types I and III fibrosis metabolism to detect cardiovascular and renal disease in chimpanzees (Pan troglodytes),” Comparative Medicine, vol. 60, no. 2, pp. 154–158, 2010.
[20]
J. J. Ely, T. Zavaskis, M. L. Lammey, M. M. Sleeper, and D. R. Lee, “Association of brain-type natriuretic protein and cardiac troponin I with incipient cardiovascular disease in chimpanzees (Pan troglodytes),” Comparative Medicine, vol. 61, no. 2, pp. 163–169, 2011.
[21]
J. J. Ely, T. Zavaskis, M. L. Lammey, and D. Rick Lee, “Blood pressure reference intervals for healthy adult chimpanzees (Pan troglodytes),” Journal of Medical Primatology, vol. 40, no. 3, pp. 171–180, 2011.
[22]
M. L. Lammey, G. B. Baskin, A. P. Gigliotti, D. R. Lee, J. J. Ely, and M. M. Sleeper, “Interstitial myocardial fibrosis in a captive chimpanzee (Pan troglodytes) population,” Comparative Medicine, vol. 58, no. 4, pp. 389–394, 2008.
[23]
B. M. Seiler, E. J. Dick, R. Guardado-Mendoza et al., “Spontaneous heart disease in the adult chimpanzee (Pan troglodytes),” Journal of Medical Primatology, vol. 38, no. 1, pp. 51–58, 2009.
[24]
M. M. Sleeper, C. J. Doane, P. H. Langner, S. Curtis, K. Avila, and D. R. Lee, “Successful treatment of idiopathic dilated cardiomyopathy in an adult chimpanzee (Pan troglodytes),” Comparative Medicine, vol. 55, no. 1, pp. 80–84, 2005.
[25]
N. Varki, D. Anderson, J. G. Herndon et al., “Heart disease is common in humans and chimpanzees, but is caused by different pathological processes,” Evolutionary Applications, vol. 2, no. 1, pp. 101–112, 2009.
[26]
M. Floris-Moore, A. A. Howard, Y. Lo, E. E. Schoenbaum, J. H. Arnsten, and R. S. Klein, “Hepatitis C infection is associated with lower lipids and high-sensitivity C-reactive protein in HIV-infected men,” AIDS Patient Care and STDs, vol. 21, no. 7, pp. 479–491, 2007.
[27]
M. M. Nascimento, A. Bruchfeld, M. E. Suliman et al., “Effect of hepatitis C serology on C-reactive protein in a cohort of Brazilian hemodialysis patients,” Brazilian Journal of Medical and Biological Research, vol. 38, no. 5, pp. 783–788, 2005.
[28]
J. I. Tsui, M. A. Whooley, A. Monto, K. Seal, P. C. Tien, and M. Shlipak, “Association of hepatitis C virus seropositivity with inflammatory markers and heart failure in persons with coronary heart disease: data from the heart and soul study,” Journal of Cardiac Failure, vol. 15, no. 5, pp. 451–456, 2009.
[29]
P. Meuleman and G. Leroux-Roels, “HCV animal models: a journey of more than 30 years,” Viruses, vol. 1, no. 2, pp. 222–240, 2009.
[30]
A. J. Lamperez and T. J. Rowell, “Normal C-reactive protein values for captive chimpanzees (Pan troglodytes),” Contemporary Topics in Laboratory Animal Science, vol. 44, no. 5, pp. 25–26, 2005.
[31]
E. K. Harris and J. C. Boyd, Bases of Reference Values in Laboratory Medicine, Marcel Dekker, New York, NY, USA, 1995.
[32]
J. J. Ely, B. Dye, W. I. Frels et al., “Subspecies composition and founder contribution of the captive U.S. Chimpanzee (Pan troglodytes) population,” American Journal of Primatology, vol. 67, no. 2, pp. 223–241, 2005.
[33]
Institute for Laboratory Animal Research, Chimpanzees in Research Strategies for their Ethical Care, Management and Use, National Academies Press, Washington, DC, USA, 1997.
[34]
Institute for Laboratory Animal Research, Guide to the Care and Use of LaboraTory Animals, National Academy Press, Washington, DC, USA, 1996.
[35]
N. Aziz, J. L. Fahey, R. Detels, and A. W. Butch, “Analytical performance of a highly sensitive C-reactive protein-based immunoassay and the effects of laboratory variables on levels of protein in blood,” Clinical and Diagnostic Laboratory Immunology, vol. 10, no. 4, pp. 652–657, 2003.
[36]
Beckman Coulter Inc., IMMAGE Immunochemistry Systems CRPH Chemistry Information Sheet, High Sensitivity C-Reactive Protein, Chemistry Information Sheet 988629 AG, 2010, http://www.beckmancoulter.com/wsrportal/search/Bernard/#2/10//0/25/1/0/asc/2/Bernard///0/1//0/.
[37]
W. L. Roberts, R. Sedrick, L. Moulton, A. Spencer, and N. Rifai, “Evaluation of four automated high-sensitivity C-reactive protein methods: implications for clinical and epidemiological applications,” Clinical Chemistry, vol. 46, no. 4, pp. 461–468, 2000.
[38]
D. A. Armbruster, M. D. Tillman, and L. M. Hubbs, “Limit of detection (LOD)/limit of quantitation (LOQ): comparison of the empirical and the statistical methods exemplified with GC-MS assays of abused drugs,” Clinical Chemistry, vol. 40, no. 7, part 1, pp. 1233–1238, 1994.
[39]
D. R. Helsel, Nondetects and Data Analysis, Wiley, New York, NY, USA, 2005.
[40]
W. L. Roberts, L. Moulton, T. C. Law et al., “Evaluation of nine automated high-sensitivity c-reactive protein methods: implications for clinical and epidemiological applications,” Clinical Chemistry, vol. 47, no. 3, pp. 418–425, 2001.
[41]
M. A. Larkin, G. Blackshields, N. P. Brown et al., “Clustal W and Clustal X version 2.0,” Bioinformatics, vol. 23, no. 21, pp. 2947–2948, 2007.
[42]
J. D. Thompson, T. J. Gibson, F. Plewniak, F. Jeanmougin, and D. G. Higgins, “The CLUSTAL X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools,” Nucleic Acids Research, vol. 25, no. 24, pp. 4876–4882, 1997.
[43]
I. A. Adzhubei, S. Schmidt, L. Peshkin et al., “A method and server for predicting damaging missense mutations,” Nature Methods, vol. 7, no. 4, pp. 248–249, 2010.
[44]
V. Ramensky, P. Bork, and S. Sunyaev, “Human non-synonymous SNPs: server and survey,” Nucleic Acids Research, vol. 30, no. 17, pp. 3894–3900, 2002.
E. L. Kaplan and P. Meier, “Nonparametric estimation from incomplete observations,” Journal of the American Statistical Association, vol. 53, pp. 457–481, 1958.
[47]
J. H. Ware and D. L. Demets, “Reanalysis of some baboon descent data,” Biometrics, vol. 32, no. 2, pp. 459–463, 1976.
[48]
D. W. Hosmer and S. Lemesow, Applied Survival Analysis, Wiley, New York, NY, USA, 1999.
[49]
J. W. Tukey, Exploratory Data Analysis, Addison-Wesley, Reading, Mass, USA, 1977.
[50]
R. Rosenthal and R. L. Rosnow, Contrast Analysis: Focused Comparisons in the Analysis of Variance, Cambridge University Press, Cambridge, UK, 1985.
[51]
G. W. Snedecor and W. G. Cochrane, Statistical Methods, Iowa State University Press, Ames, Iowa, USA, 6th edition, 1967.
[52]
R. H. Friis and T. A. Sellers, Epidemiology For Public Health Practice, Jones and Bartlett, Sudbury, Canada, 4th edition, 2009.
[53]
R. Clarke, J. R. Emberson, E. Breeze et al., “Biomarkers of inflammation predict both vascular and non-vascular mortality in older men,” European Heart Journal, vol. 29, no. 6, pp. 800–809, 2008.
[54]
E. S. Ford, W. H. Giles, G. L. Myers, N. Rifai, P. M. Ridker, and D. M. Mannino, “C-reactive protein concentration distribution among US children and young adults: findings from the National Health and Nutrition Examination Survey, 1999-2000,” Clinical Chemistry, vol. 49, no. 8, pp. 1353–1357, 2003.
[55]
E. M. Macy, T. E. Hayes, and R. P. Tracy, “Variability in the measurement of C-reactive protein in healthy subjects: implications for reference intervals and epidemiological applications,” Clinical Chemistry, vol. 43, no. 1, pp. 52–58, 1997.
[56]
H. Solberg and R. Gr？sbeck, “Reference values,” Advances in Clinical Chemistry, vol. 27, pp. 1–79, 1989.
[57]
A. Agresti, Categorical Data Analysis, John Wiley & Sons, Hoboken, NJ, USA, 2nd edition, 2002.
[58]
S. E. Fienberg, The Analysis of Cross-Classified Categorical Data, MIT Press, Cambridge, Mass, USA, 2nd edition, 1980.
[59]
C. N. Kroll and J. R. Stedinger, “Estimation of moments and quantiles using censored data,” Water Resources Research, vol. 32, no. 4, pp. 1005–1012, 1996.
[60]
A. Rispin, D. Farrar, E. Margosches et al., “Alternative methods for the median lethal dose (LD50) test: the up-and-down procedure for acute oral toxicity,” ILAR Journal, vol. 43, no. 4, pp. 233–243, 2002.
[61]
R. J. A. Little, “A test of missing completely at random for multivariate data with missing values,” Journal of the American Statistical Association, vol. 83, pp. 1198–1202, 1988.
[62]
R. C. Antweiler and H. E. Taylor, “Evaluation of statistical treatments of left-censored environmental data using coincident uncensored data sets: I. Summary statistics,” Environmental Science and Technology, vol. 42, no. 10, pp. 3732–3738, 2008.
[63]
P. Hougaard, Analysis of Multivariate Survival Data, Springer, New York, NY, USA, 2000.
[64]
R. J. Glynn, N. M. Laird, and D. B. Rubin, “Multiple imputation in mixture models for nonignorable nonresponse with follow-ups,” Journal of the American Statistical Association, vol. 88, no. 423, pp. 984–993, 1993.
[65]
A. R. T. Donders, G. J. M. G. van der Heijden, T. Stijnen, and K. G. M. Moons, “Review: a gentle introduction to imputation of missing values,” Journal of Clinical Epidemiology, vol. 59, no. 10, pp. 1087–1091, 2006.
[66]
N. J. Horton and K. P. Kleinman, “Much ado about nothing: a comparison of missing data methods and software to fit incomplete data regression models,” American Statistician, vol. 61, no. 1, pp. 79–90, 2007.
[67]
P. S. Horn, A. J. Pesce, and B. E. Copeland, “A robust approach to reference interval estimation and evaluation,” Clinical Chemistry, vol. 44, no. 3, pp. 622–631, 1998.
[68]
M. M. Finkelstein and D. K. Verma, “Exposure estimation in the presence of nondetectable values: another look,” American Industrial Hygiene Association Journal, vol. 62, no. 2, pp. 195–198, 2001.
[69]
P. Wessa, “Free Statistics Software, Office for Research Development and Education, version 1. 1. 23-r7,” 2012, http://www.wessa.net/.
[70]
M. A. Stephens, “EDF statistics for goodness of fit and some comparisons,” Journal of the American Statistical Association, vol. 69, pp. 730–737, 1974.
[71]
L. Fu and Y. G. Wang, “Nonparametric rank regression for analyzing water quality concentration data with multiple detection limits,” Environmental Science and Technology, vol. 45, no. 4, pp. 1481–1489, 2011.
[72]
W. G. Wood, J. Lüdemann, R. Mitusch, J. Heinrich, R. Maass, and U. Frick, “Evaluation of a sensitive immunoluminometric assay for the determination of C-reactive protein (CRP) in serum and plasma and the establishment of reference ranges for different groups of subjects,” Clinical Laboratory, vol. 46, no. 3-4, pp. 131–140, 2000.
[73]
J. L. Schafer, “Software for multiple imputation,” 2000, http://sites.stat.psu.edu/~jls/misoftwa.html.
[74]
I. G. N. Darmawan, “NORM software review: handling missing values with multiple imputation methods,” Evaluation Journal of Australasia, vol. 2, no. 1, pp. 51–57, 2002.
[75]
D. C. Howell, “Multiple imputation using NORM,” 2010, http://www.uvm.edu/~dhowell/StatPages/More_Stuff/Missing_Data/MissingDataWith%20NORM/NormMissingData.html.
[76]
D. Rubin, ,Multiple Imputation for Nonresponse in Surveys, Wiley, New York, NY, USA, 1987.
[77]
J. L. Schafer, Analysis of Incomplete Multivariate Data, Chapman & Hall, London, UK, 1997.
[78]
J. B. Carlin, N. Li, P. Greenwood, and C. Coffey, “Tools for analyzing multiple imputed datasets,” Stata Journal, vol. 3, no. 3, pp. 226–244, 2003.
[79]
E. K. Harris and J. C. Boyd, “On dividing reference data into subgroups to produce separate reference ranges,” Clinical Chemistry, vol. 36, no. 2, pp. 265–270, 1990.
[80]
P. S. Horn and A. J. Pesce, Reference IntervalS: A USer'S Guide, AACC Press, Washington, DC, USA, 2005.
[81]
F. E. Harrell and C. E. Davis, “A new distribution-free quantile estimator,” Biometrika, vol. 69, no. 3, pp. 635–640, 1982.
[82]
A. D. Hutson and M. D. Ernst, “The exact bootstrap mean and variance of an L-estimator,” Journal of the Royal Statistical Society B, vol. 62, no. 1, pp. 89–94, 2000.
[83]
Clinical and Laboratory Standards Institute, Defining, Establishing, and Verifying Reference Intervals in the Clinical Laboratory, Approved Guidelines, CLSI document C28-A3, Fort Wayne, Ind, USA, 3rd edition, 2008.
S. L. Stockman and M. A. Scott, Fundamentals of Veterinary Clinical Pathology, Wiley, New York, NY, USA, 2nd edition, 2008.
[86]
R. Zhang, Y. Y. Zhang, X. R. Huang et al., “C-reactive protein promotes cardiac fibrosis and inflammation in angiotensin II-induced hypertensive cardiac disease,” Hypertension, vol. 55, no. 4, pp. 953–960, 2010.
[87]
E. J. Erlandsen and E. Randers, “Reference interval for serum C-reactive protein in healthy blood donors using the Dade Behring N Latex CRP mono assay,” Scandinavian Journal of Clinical and Laboratory Investigation, vol. 60, no. 1, pp. 37–44, 2000.
[88]
B. Herbeth, G. Siest, and J. Henny, “High sensitivity C-reactive protein (CRP) reference intervals in the elderly,” Clinical Chemistry and Laboratory Medicine, vol. 39, no. 11, pp. 1169–1170, 2001.
[89]
M. B. Pepys and G. M. Hirschfield, “C-reactive protein: a critical update,” Journal of Clinical Investigation, vol. 111, no. 12, pp. 1805–1812, 2003.
[90]
O. Chenillot, J. Henny, J. Steinmetz, B. Herbeth, C. Wagner, and G. Siest, “High sensitivity C-reactive protein: biological variations and reference limits,” Clinical Chemistry and Laboratory Medicine, vol. 38, no. 10, pp. 1003–1011, 2000.
[91]
S. P. Fortmann, E. Ford, M. H. Criqui et al., “CDC/AHA workshop on markers of inflammation and cardiovascular disease,” Circulation, vol. 110, no. 25, pp. e554–e559, 2004.
[92]
H. Schlebusch, N. Liappis, E. Kalina, and C. Klein, “High sensitive CRP and creatinine: reference intervals from infancy to childhood,” LaboratoriumsMedizin, vol. 26, no. 5-6, pp. 341–346, 2002.
[93]
Z. Wang and W. E. Hoy, “Population distribution of high sensitivity C-reactive protein values in Aboriginal Australians: a comparison with other populations,” Clinical Biochemistry, vol. 39, no. 3, pp. 277–281, 2006.
