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Osteoporosis International
Published in: Osteoporosis International 4/2014

01-04-2014 | Original Article

Dissecting the relationship between high-sensitivity serum C-reactive protein and increased fracture risk: the Rotterdam Study

Authors: L. Oei, N. Campos-Obando, A. Dehghan, E. H. G. Oei, L. Stolk, J. B. J. van Meurs, A. Hofman, A. G. Uitterlinden, O. H. Franco, M. C. Zillikens, F. Rivadeneira

Published in: Osteoporosis International | Issue 4/2014

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Abstract

Summary

Serum high-sensitivity C-reactive protein (CRP) is an inflammatory biomarker. We investigated the relationship between CRP and bone health in the Rotterdam Study. Serum high-sensitivity CRP was associated with fracture risk and lower femoral neck bending strength. Mendelian randomization analyses did not yield evidence for this relationship being causal.

Introduction

Inflammatory diseases are associated with bone pathology, reflected in a higher fracture risk. Serum high-sensitivity CRP is an inflammatory biomarker. We investigated the relationship between CRP and bone mineral density (BMD), hip bone geometry, and incident fractures in the Rotterdam Study, a prospective population-based cohort.

Methods

At baseline, serum high-sensitivity CRP was measured. A weighted genetic risk score was compiled for CRP based on published studies (29 polymorphisms; Illumina HumanHap550 Beadchip genotyping and HapMap imputation). Regression models were reported per standard deviation increase in CRP adjusted for sex, age, and BMI. Complete data was available for 6,386 participants, of whom 1,561 persons sustained a fracture (mean follow-up, 11.6 years).

Results

CRP was associated with a risk for any type of fracture [hazard ratio (HR) = 1.06; 95 % confidence interval (CI), 1.02–1.11], hip fractures (HR = 1.09; 1.02–1.17) and vertebral fractures [odds ratio (OR) = 1.34; 1.14–1.58]. An inverse relationship between CRP levels and section modulus (−0.011 cm3; −0.020 to −0.003 cm3) was observed. The combined genetic risk score of CRP single nucleotide polymorphisms (SNPs) was associated with serum CRP levels (p = 9 × 10−56), but not with fracture risk (HR = 1.00; 0.99–1.00; p = 0.23).

Conclusions

Serum high-sensitivity CRP is associated with fracture risk and lower bending strength. Mendelian randomization analyses did not yield evidence for this relationship being causal. Future studies might reveal what factors truly underlie the relationship between CRP and fracture risk.
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Literature
1.
2.
Pasco JA, Kotowicz MA, Henry MJ, Nicholson GC, Spilsbury HJ, Box JD, Schneider HG (2006) High-sensitivity C-reactive protein and fracture risk in elderly women. JAMA 296:1353–1355PubMedCrossRef
3.
4.
5.
de Pablo P, Cooper MS, Buckley CD (2012) Association between bone mineral density and C-reactive protein in a large population-based sample. Arthritis Rheum 64:2624–2631PubMedCrossRef
6.
Ding C, Parameswaran V, Udayan R, Burgess J, Jones G (2008) Circulating levels of inflammatory markers predict change in bone mineral density and resorption in older adults: a longitudinal study. J Clin Endocrinol Metab 93:1952–1958PubMedCrossRef
7.
Koh JM, Khang YH, Jung CH, Bae S, Kim DJ, Chung YE, Kim GS (2005) Higher circulating hsCRP levels are associated with lower bone mineral density in healthy pre- and postmenopausal women: evidence for a link between systemic inflammation and osteoporosis. Osteoporos Int 16:1263–1271PubMedCrossRef
8.
Rolland T, Boutroy S, Vilayphiou N, Blaizot S, Chapurlat R, Szulc P (2012) Poor trabecular microarchitecture at the distal radius in older men with increased concentration of high-sensitivity C-reactive protein—the STRAMBO study. Calcif Tissue Int 90:496–506PubMedCrossRef
9.
Ganesan K, Teklehaimanot S, Tran TH, Asuncion M, Norris K (2005) Relationship of C-reactive protein and bone mineral density in community-dwelling elderly females. J Natl Med Assoc 97:329–333PubMedCentralPubMed
10.
Ebrahim S, Davey Smith G (2008) Mendelian randomization: can genetic epidemiology help redress the failures of observational epidemiology? Hum Genet 123:15–33PubMedCrossRef
11.
Didelez V, Sheehan N (2007) Mendelian randomization as an instrumental variable approach to causal inference. Stat Methods Med Res 16:309–330PubMedCrossRef
12.
Gray R, Wheatley K (1991) How to avoid bias when comparing bone-marrow transplantation with chemotherapy. Bone Marrow Transplant 7:9–12PubMed
13.
Dupuis J, Larson MG, Vasan RS, Massaro JM, Wilson PW, Lipinska I, Corey D, Vita JA, Keaney JF Jr, Benjamin EJ (2005) Genome scan of systemic biomarkers of vascular inflammation in the Framingham Heart Study: evidence for susceptibility loci on 1q. Atherosclerosis 182:307–314PubMedCrossRef
14.
Pankow JS, Folsom AR, Cushman M, Borecki IB, Hopkins PN, Eckfeldt JH, Tracy RP (2001) Familial and genetic determinants of systemic markers of inflammation: the NHLBI family heart study. Atherosclerosis 154:681–689PubMedCrossRef
15.
Retterstol L, Eikvar L, Berg K (2003) A twin study of C-reactive protein compared to other risk factors for coronary heart disease. Atherosclerosis 169:279–282PubMedCrossRef
16.
Dehghan A, Dupuis J, Barbalic M et al (2011) Meta-analysis of genome-wide association studies in >80 000 subjects identifies multiple loci for C-reactive protein levels. Circulation 123:731–738PubMedCentralPubMedCrossRef
17.
Zacho J, Tybjaerg-Hansen A, Jensen JS, Grande P, Sillesen H, Nordestgaard BG (2008) Genetically elevated C-reactive protein and ischemic vascular disease. N Engl J Med 359:1897–1908PubMedCrossRef
18.
19.
Dehghan A, Kardys I, de Maat MP, Uitterlinden AG, Sijbrands EJ, Bootsma AH, Stijnen T, Hofman A, Schram MT, Witteman JC (2007) Genetic variation, C-reactive protein levels, and incidence of diabetes. Diabetes 56:872–878PubMedCrossRef
20.
McCloskey EV, Spector TD, Eyres KS, Fern ED, O’Rourke N, Vasikaran S, Kanis JA (1993) The assessment of vertebral deformity: a method for use in population studies and clinical trials. Osteoporos Int 3:138–147PubMedCrossRef
21.
Van der Klift M, De Laet CE, McCloskey EV, Hofman A, Pols HA (2002) The incidence of vertebral fractures in men and women: the Rotterdam Study. J Bone Miner Res 17:1051–1056PubMedCrossRef
22.
Burger H, de Laet CE, van Daele PL, Weel AE, Witteman JC, Hofman A, Pols HA (1998) Risk factors for increased bone loss in an elderly population: the Rotterdam Study. Am J Epidemiol 147:871–879PubMedCrossRef
23.
Beck TJ, Looker AC, Ruff CB, Sievanen H, Wahner HW (2000) Structural trends in the aging femoral neck and proximal shaft: analysis of the Third National Health and Nutrition Examination Survey dual-energy X-ray absorptiometry data. J Bone Miner Res 15:2297–2304PubMedCrossRef
24.
Rivadeneira F, Zillikens MC, De Laet CE, Hofman A, Uitterlinden AG, Beck TJ, Pols HA (2007) Femoral neck BMD is a strong predictor of hip fracture susceptibility in elderly men and women because it detects cortical bone instability: the Rotterdam Study. J Bone Miner Res 22:1781–1790PubMedCrossRef
25.
Pincus T, Summey JA, Soraci SA Jr, Wallston KA, Hummon NP (1983) Assessment of patient satisfaction in activities of daily living using a modified Stanford Health Assessment Questionnaire. Arthritis Rheum 26:1346–1353PubMedCrossRef
26.
Odding E, Valkenburg HA, Algra D, Vandenouweland FA, Grobbee DE, Hofman A (1995) Association of locomotor complaints and disability in the Rotterdam study. Ann Rheum Dis 54:721–725PubMedCentralPubMedCrossRef
27.
International HapMap Consortium (2003) The International HapMap Project. Nature 426:789–796CrossRef
28.
Altshuler DM, Gibbs RA, Peltonen L et al (2010) Integrating common and rare genetic variation in diverse human populations. Nature 467:52–58PubMedCrossRef
29.
Erlinger TP, Platz EA, Rifai N, Helzlsouer KJ (2004) C-reactive protein and the risk of incident colorectal cancer. JAMA 291:585–590PubMedCrossRef
30.
Danesh J, Wheeler JG, Hirschfield GM, Eda S, Eiriksdottir G, Rumley A, Lowe GD, Pepys MB, Gudnason V (2004) C-reactive protein and other circulating markers of inflammation in the prediction of coronary heart disease. N Engl J Med 350:1387–1397PubMedCrossRef
31.
Pradhan AD, Manson JE, Rifai N, Buring JE, Ridker PM (2001) C-reactive protein, interleukin 6, and risk of developing type 2 diabetes mellitus. JAMA 286:327–334PubMedCrossRef
32.
Brunner EJ, Kivimaki M, Witte DR et al (2008) Inflammation, insulin resistance, and diabetes—Mendelian randomization using CRP haplotypes points upstream. PLoS Med 5:e155PubMedCentralPubMedCrossRef
33.
Dirven L, van den Broek M, van Groenendael JH, de Beus WM, Kerstens PJ, Huizinga TW, Allaart CF, Lems WF (2012) Prevalence of vertebral fractures in a disease activity steered cohort of patients with early active rheumatoid arthritis. BMC Musculoskelet Disord 13:125PubMedCentralPubMedCrossRef
34.
Orstavik RE, Haugeberg G, Mowinckel P, Hoiseth A, Uhlig T, Falch JA, Halse JI, McCloskey E, Kvien TK (2004) Vertebral deformities in rheumatoid arthritis: a comparison with population-based controls. Arch Intern Med 164:420–425PubMedCrossRef
35.
van Staa TP, Cooper C, Brusse LS, Leufkens H, Javaid MK, Arden NK (2003) Inflammatory bowel disease and the risk of fracture. Gastroenterology 125:1591–1597PubMedCrossRef
36.
Mitra D, Elvins DM, Speden DJ, Collins AJ (2000) The prevalence of vertebral fractures in mild ankylosing spondylitis and their relationship to bone mineral density. Rheumatology (Oxford) 39:85–89CrossRef
37.
van der Weijden MA, van der Horst-Bruinsma IE, van Denderen JC, Dijkmans BA, Heymans MW, Lems WF (2012) High frequency of vertebral fractures in early spondylarthropathies. Osteoporos Int 23:1683–1690PubMedCrossRef
38.
van der Weijden MA, Claushuis TA, Nazari T, Lems WF, Dijkmans BA, van der Horst-Bruinsma IE (2012) High prevalence of low bone mineral density in patients within 10 years of onset of ankylosing spondylitis: a systematic review. Clin Rheumatol 31:1529–1535PubMedCentralPubMedCrossRef
39.
Alele JD, Kamen DL, Hunt KJ, Ramsey-Goldman R (2011) Bone geometry profiles in women with and without SLE. J Bone Miner Res 26:2719–2726PubMedCrossRef
40.
Oei L, Zillikens MC, Dehghan A et al (2013) High bone mineral density and fracture risk in type 2 diabetes as skeletal complications of inadequate glucose control: the Rotterdam Study. Diabetes Care 36:1619–1628PubMedCrossRef
41.
Ma L, Oei L, Jiang L, Estrada K, Chen H, Wang Z, Yu Q, Zillikens MC, Gao X, Rivadeneira F (2012) Association between bone mineral density and type 2 diabetes mellitus: a meta-analysis of observational studies. Eur J Epidemiol 27:319–332PubMedCentralPubMedCrossRef
42.
Ishii S, Cauley JA, Greendale GA, Crandall CJ, Danielson ME, Ouchi Y, Karlamangla AS (2013) C-reactive protein, bone strength, and nine-year fracture risk: data from the Study of Women’s Health Across the Nation (SWAN). J Bone Miner Res 28:1688–1698PubMedCrossRef
43.
Quinn JM, Gillespie MT (2005) Modulation of osteoclast formation. Biochem Biophys Res Commun 328:739–745PubMedCrossRef
44.
Tanabe N, Ito-Kato E, Suzuki N, Nakayama A, Ogiso B, Maeno M, Ito K (2004) IL-1alpha affects mineralized nodule formation by rat osteoblasts. Life Sci 75:2317–2327PubMedCrossRef
45.
den Uyl D, Bultink IE, Lems WF (2011) Glucocorticoid-induced osteoporosis. Clin Exp Rheumatol 29:S93–98
46.
Canalis E, Mazziotti G, Giustina A, Bilezikian JP (2007) Glucocorticoid-induced osteoporosis: pathophysiology and therapy. Osteoporos Int 18:1319–1328PubMedCrossRef
47.
Kaji H, Yamauchi M, Chihara K, Sugimoto T (2008) Glucocorticoid excess affects cortical bone geometry in premenopausal, but not postmenopausal, women. Calcif Tissue Int 82:182–190PubMedCrossRef
48.
Pierce BL, Ahsan H, Vanderweele TJ (2011) Power and instrument strength requirements for Mendelian randomization studies using multiple genetic variants. Int J Epidemiol 40:740–752PubMedCentralPubMedCrossRef
Metadata
Title
Dissecting the relationship between high-sensitivity serum C-reactive protein and increased fracture risk: the Rotterdam Study
Authors
L. Oei
N. Campos-Obando
A. Dehghan
E. H. G. Oei
L. Stolk
J. B. J. van Meurs
A. Hofman
A. G. Uitterlinden
O. H. Franco
M. C. Zillikens
F. Rivadeneira
Publication date
01-04-2014
Publisher
Springer London
Published in
Osteoporosis International / Issue 4/2014
Print ISSN: 0937-941X
Electronic ISSN: 1433-2965
DOI
https://doi.org/10.1007/s00198-013-2578-0

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