#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Predicting the Risk of Rheumatoid Arthritis and Its Age of Onset through Modelling Genetic Risk Variants with Smoking


The improved characterisation of risk factors for rheumatoid arthritis (RA) suggests they could be combined to identify individuals at increased disease risks in whom preventive strategies may be evaluated. We aimed to develop an RA prediction model capable of generating clinically relevant predictive data and to determine if it better predicted younger onset RA (YORA). Our novel modelling approach combined odds ratios for 15 four-digit/10 two-digit HLA-DRB1 alleles, 31 single nucleotide polymorphisms (SNPs) and ever-smoking status in males to determine risk using computer simulation and confidence interval based risk categorisation. Only males were evaluated in our models incorporating smoking as ever-smoking is a significant risk factor for RA in men but not women. We developed multiple models to evaluate each risk factor's impact on prediction. Each model's ability to discriminate anti-citrullinated protein antibody (ACPA)-positive RA from controls was evaluated in two cohorts: Wellcome Trust Case Control Consortium (WTCCC: 1,516 cases; 1,647 controls); UK RA Genetics Group Consortium (UKRAGG: 2,623 cases; 1,500 controls). HLA and smoking provided strongest prediction with good discrimination evidenced by an HLA-smoking model area under the curve (AUC) value of 0.813 in both WTCCC and UKRAGG. SNPs provided minimal prediction (AUC 0.660 WTCCC/0.617 UKRAGG). Whilst high individual risks were identified, with some cases having estimated lifetime risks of 86%, only a minority overall had substantially increased odds for RA. High risks from the HLA model were associated with YORA (P<0.0001); ever-smoking associated with older onset disease. This latter finding suggests smoking's impact on RA risk manifests later in life. Our modelling demonstrates that combining risk factors provides clinically informative RA prediction; additionally HLA and smoking status can be used to predict the risk of younger and older onset RA, respectively.


Vyšlo v časopise: Predicting the Risk of Rheumatoid Arthritis and Its Age of Onset through Modelling Genetic Risk Variants with Smoking. PLoS Genet 9(9): e32767. doi:10.1371/journal.pgen.1003808
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1003808

Souhrn

The improved characterisation of risk factors for rheumatoid arthritis (RA) suggests they could be combined to identify individuals at increased disease risks in whom preventive strategies may be evaluated. We aimed to develop an RA prediction model capable of generating clinically relevant predictive data and to determine if it better predicted younger onset RA (YORA). Our novel modelling approach combined odds ratios for 15 four-digit/10 two-digit HLA-DRB1 alleles, 31 single nucleotide polymorphisms (SNPs) and ever-smoking status in males to determine risk using computer simulation and confidence interval based risk categorisation. Only males were evaluated in our models incorporating smoking as ever-smoking is a significant risk factor for RA in men but not women. We developed multiple models to evaluate each risk factor's impact on prediction. Each model's ability to discriminate anti-citrullinated protein antibody (ACPA)-positive RA from controls was evaluated in two cohorts: Wellcome Trust Case Control Consortium (WTCCC: 1,516 cases; 1,647 controls); UK RA Genetics Group Consortium (UKRAGG: 2,623 cases; 1,500 controls). HLA and smoking provided strongest prediction with good discrimination evidenced by an HLA-smoking model area under the curve (AUC) value of 0.813 in both WTCCC and UKRAGG. SNPs provided minimal prediction (AUC 0.660 WTCCC/0.617 UKRAGG). Whilst high individual risks were identified, with some cases having estimated lifetime risks of 86%, only a minority overall had substantially increased odds for RA. High risks from the HLA model were associated with YORA (P<0.0001); ever-smoking associated with older onset disease. This latter finding suggests smoking's impact on RA risk manifests later in life. Our modelling demonstrates that combining risk factors provides clinically informative RA prediction; additionally HLA and smoking status can be used to predict the risk of younger and older onset RA, respectively.


Zdroje

1. WolfeF, HawleyDJ (1998) The longterm outcomes of rheumatoid arthritis: Work disability: a prospective 18 year study of 823 patients. J Rheumatol 25: 2108–2117.

2. MichaudK, MesserJ, ChoiHK, WolfeF (2003) Direct medical costs and their predictors in patients with rheumatoid arthritis: a three-year study of 7,527 patients. Arthritis Rheum 48: 2750–2762.

3. ScottDL, WolfeF, HuizingaTWJ (2010) Rheumatoid arthritis. Lancet 376: 1094–1108.

4. EyreS, BowesJ, DiogoD, LeeA, BartonA, et al. (2012) High-density genetic mapping identifies new susceptibility loci for rheumatoid arthritis. Nat Genet 44: 1336–1340.

5. SugiyamaD, NishimuraK, TamakiK, TsujiG, NakazawaT, et al. (2010) Impact of smoking as a risk factor for developing rheumatoid arthritis: a meta-analysis of observational studies. Ann Rheum Dis 69: 70–81.

6. PedersenM, JacobsenS, GarredP, MadsenHO, KlarlundM, et al. (2007) Strong combined gene-environment effects in anti-cyclic citrullinated peptide-positive rheumatoid arthritis: a nationwide case-control study in Denmark. Arthritis Rheum 56: 1446–1453.

7. KallbergH, PadyukovL, PlengeRM, RonnelidJ, GregersenPK, et al. (2007) Gene-gene and gene-environment interactions involving HLA-DRB1, PTPN22, and smoking in two subsets of rheumatoid arthritis. Am J Hum Genet 80: 867–875.

8. SchulzeMB, WeikertC, PischonT, BergmannMM, Al-HasaniH, et al. (2009) Use of multiple metabolic and genetic markers to improve the prediction of type 2 diabetes: the EPIC-Potsdam Study. Diabetes Care 32: 2116–2119.

9. TalmudPJ, HingoraniAD, CooperJA, MarmotMG, BrunnerEJ, et al. (2010) Utility of genetic and non-genetic risk factors in prediction of type 2 diabetes: Whitehall II prospective cohort study. BMJ 340: b4838.

10. PaynterNP, ChasmanDI, PareG, BuringJE, CookNR, et al. (2010) Association between a literature-based genetic risk score and cardiovascular events in women. JAMA 303: 631–637.

11. GerlagDM, RazaK, van BaarsenLGM, BrouwerE, BuckleyCD, et al. (2012) EULAR recommendations for terminology and research in individuals at risk of rheumatoid arthritis: report from the Study Group for Risk Factors for Rheumatoid Arthritis. Ann Rheum Dis 71: 638–641.

12. NielenMMJ, van SchaardenburgD, ReesinkHW, van de StadtRJ, van der Horst-BruinsmaIE, et al. (2004) Specific autoantibodies precede the symptoms of rheumatoid arthritis: a study of serial measurements in blood donors. Arthritis Rheum 50: 380–386.

13. BosWH, DijkmansBAC, BoersM, van de StadtRJ, van SchaardenburgD (2010) Effect of dexamethasone on autoantibody levels and arthritis development in patients with arthralgia: a randomised trial. Ann Rheum Dis 69: 571–574.

14. VerstappenSM, McCoyMJ, RobertsC, DaleNE, HassellAB, et al. (2010) Beneficial effects of a 3-week course of intramuscular glucocorticoid injections in patients with very early inflammatory polyarthritis: results of the STIVEA trial. Ann Rheum Dis 69: 503–509.

15. van DongenH, van AkenJ, LardLR, VisserK, RondayHK, et al. (2007) Efficacy of methotrexate treatment in patients with probable rheumatoid arthritis: a double-blind, randomized, placebo-controlled trial. Arthritis Rheum 56: 1424–1432.

16. EmeryP, DurezP, DougadosM, LegertonCW, BeckerJC, et al. (2010) Impact of T-cell costimulation modulation in patients with undifferentiated inflammatory arthritis or very early rheumatoid arthritis: a clinical and imaging study of abatacept (the ADJUST trial). Ann Rheum Dis 69: 510–516.

17. LajasC, AbasoloL, BellajdelB, Hernandez-GarciaC, CarmonaL, et al. (2003) Costs and predictors of costs in rheumatoid arthritis: a prevalence-based study. Arthritis Rheum 49: 64–70.

18. HellierJP, EliaouJF, DauresJP, SanyJ, CombeB (2001) HLA-DRB1 genes and patients with late onset rheumatoid arthritis. Ann Rheum Dis 60: 531–533.

19. WuH, KhannaD, ParkG, GersukV, NepomGT, et al. (2004) Interaction between RANKL and HLA-DRB1 genotypes may contribute to younger age at onset of seropositive rheumatoid arthritis in an inception cohort. Arthritis Rheum 50: 3093–3103.

20. JaraquemadaD, OllierW, AwadJ, YoungA, SilmanA, et al. (1986) HLA and rheumatoid arthritis: a combined analysis of 440 British patients. Ann Rheum Dis 45: 627–636.

21. MacGregorA, OllierW, ThomsonW, JawaheerD, SilmanA (1995) HLA-DRB1*0401/0404 genotype and rheumatoid arthritis: increased association in men, young age at onset, and disease severity. J Rheumatol 22: 1032–1036.

22. ChenY, MatteyDL (2012) Age at onset of rheumatoid arthritis: association with polymorphisms in the vascular endothelial growth factor A(VEGFA) gene and an intergenic locus between matrix metalloproteinase (MMP) 1 and 3 genes. Clin Exp Rheumatol 30: 894–898.

23. TanW, WuH, ZhaoJ, DerberLA, LeeDM, et al. (2010) A functional RANKL polymorphism associated with younger age at onset of rheumatoid arthritis. Arthritis Rheum 62: 2864–2875.

24. SteerS, LadB, GrumleyJA, KingsleyGH, FisherSA (2005) Association of R602W in a protein tyrosine phosphatase gene with a high risk of rheumatoid arthritis in a British population: evidence for an early onset/disease severity effect. Arthritis Rheum 52: 358–360.

25. KarlsonEW, ChibnikLB, CuiJ, PlengeRM, GlassRJ, et al. (2008) Associations between human leukocyte antigen, PTPN22, CTLA4 genotypes and rheumatoid arthritis phenotypes of autoantibody status, age at diagnosis and erosions in a large cohort study. Ann Rheum Dis 67: 358–363.

26. KarlsonEW, ChibnikLB, KraftP, CuiJ, KeenanBT, et al. (2010) Cumulative association of 22 genetic variants with seropositive rheumatoid arthritis risk. Ann Rheum Dis 69: 1077–1085.

27. ChibnikLB, KeenanBT, CuiJ, LiaoKP, CostenbaderKH, et al. (2011) Genetic risk score predicting risk of rheumatoid arthritis phenotypes and age of symptom onset. PLoS ONE [Electronic Resource] 6: e24380.

28. Wellcome Trust Case Control Consortium (2007) Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447: 661–678.

29. MorganAW, ThomsonW, MartinSG (2009) Yorkshire Early Arthritis Register Consortium (2009) CarterAM, et al. (2009) Reevaluation of the interaction between HLA-DRB1 shared epitope alleles, PTPN22, and smoking in determining susceptibility to autoantibody-positive and autoantibody-negative rheumatoid arthritis in a large UK Caucasian population. Arthritis Rheum 60: 2565–2576.

30. ArnettFC, EdworthySM, BlochDA, McShaneDJ, FriesJF, et al. (1988) The American Rheumatism Association 1987 revised criteria for the classification of rheumatoid arthritis. Arthritis Rheum 31: 315–324.

31. MacGregorAJ, SniederH, RigbyAS, KoskenvuoM, KaprioJ, et al. (2000) Characterizing the quantitative genetic contribution to rheumatoid arthritis using data from twins. Arthritis Rheum 43: 30–37.

32. GoddardGHM, LewisCM (2010) Risk categorization for complex disorders according to genotype relative risk and precision in parameter estimates. Genet Epidemiol 34: 624–632.

33. CrouchDJ, GoddardGH, LewisCM (2013) REGENT: a risk assessment and classification algorithm for genetic and environmental factors. Eur J Hum Genet 21: 109–111.

34. StahlEA, RaychaudhuriS, RemmersEF, XieG, EyreS, et al. (2010) Genome-wide association study meta-analysis identifies seven new rheumatoid arthritis risk loci. Nat Genet 42: 508–514.

35. RaychaudhuriS, SandorC, StahlEA, FreudenbergJ, LeeH-S, et al. (2012) Five amino acids in three HLA proteins explain most of the association between MHC and seropositive rheumatoid arthritis. Nat Genet 44: 291–296.

36. ScottIC, TanR, StahlD, SteerS, LewisCM, et al. (2013) The Protective Effect Of Alcohol On Developing Rheumatoid Arthritis: A Systematic Review And Meta-Analysis. Rheumatology (Oxford) [Epub ahead of print]

37. KallbergH, DingB, PadyukovL, BengtssonC, RonnelidJ, et al. (2011) Smoking is a major preventable risk factor for rheumatoid arthritis: estimations of risks after various exposures to cigarette smoke. Ann Rheum Dis 70: 508–511.

38. KarlsonEW, ChangSC, CuiJ, ChibnikLB, FraserPA, et al. (2010) Gene-environment interaction between HLA-DRB1 shared epitope and heavy cigarette smoking in predicting incident rheumatoid arthritis. Ann Rheum Dis 69: 54–60.

39. JohnsonAD, HandsakerRE, PulitSL, NizzariMM, O'DonnellCJ, et al. (2008) SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap. Bioinformatics 24: 2938–2939.

40. MetzCE (1978) Basic principles of ROC analysis. Seminars in Nuclear Medicine 8: 283–298.

41. LuQ, ElstonRC (2008) Using the optimal receiver operating characteristic curve to design a predictive genetic test, exemplified with type 2 diabetes. Am J Hum Genet 82: 641–651.

42. DeLongER, DeLongDM, Clarke-PearsonDL (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44: 837–845.

43. RobinX, TurckN, HainardA, TibertiN, LisacekF, et al. (2011) pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics 12: 77.

44. SymmonsD, TurnerG, WebbR, AstenP, BarrettE, et al. (2002) The prevalence of rheumatoid arthritis in the United Kingdom: new estimates for a new century. Rheumatology (Oxford) 41: 793–800.

45. ZhangJ, YuKF (1998) What's the relative risk? A method of correcting the odds ratio in cohort studies of common outcomes. JAMA 280: 1690–1691.

46. CrowsonCS, MattesonEL, MyasoedovaE, MichetCJ, ErnsteFC, et al. (2011) The lifetime risk of adult-onset rheumatoid arthritis and other inflammatory autoimmune rheumatic diseases. Arthritis Rheum 63: 633–639.

47. HessKR (1995) Graphical methods for assessing violations of the proportional hazards assumption in Cox regression. Stat Med 14: 1707–1723.

48. HuizingaTWJ, AmosCI, van der Helm-van MilAHM, ChenW, van GaalenFA, et al. (2005) Refining the complex rheumatoid arthritis phenotype based on specificity of the HLA-DRB1 shared epitope for antibodies to citrullinated proteins. Arthritis Rheum 52: 3433–3438.

49. OrozcoG, Pascual-SalcedoD, Lopez-NevotMA, CoboT, CabezonA, et al. (2008) Auto-antibodies, HLA and PTPN22: susceptibility markers for rheumatoid arthritis. Rheumatology (Oxford) 47: 138–141.

50. KlareskogL, StoltP, LundbergK, KallbergH, BengtssonC, et al. (2006) A new model for an etiology of rheumatoid arthritis: smoking may trigger HLA-DR (shared epitope)-restricted immune reactions to autoantigens modified by citrullination. Arthritis Rheum 54: 38–46.

51. PlengeRM (2009) Recent progress in rheumatoid arthritis genetics: one step towards improved patient care. Curr Opin Rheumatol 21: 262–271.

52. de VriesRRP, van der WoudeD, HouwingJJ, ToesREM (2011) Genetics of ACPA-positive rheumatoid arthritis: the beginning of the end? Ann Rheum Dis 70 Suppl 1: i51–54.

53. WolfeF, KleinhekselSM, KhanMA (1988) Prevalence of familial occurrence in patients with rheumatoid arthritis. Br J Rheumatol 27 Suppl 2: 150–152.

54. DeightonCM, WentzelJ, CavanaghG, RobertsDF, WalkerDJ (1992) Contribution of inherited factors to rheumatoid arthritis. Ann Rheum Dis 51: 182–185.

55. KoumantakiY, GiziakiE, LinosA, KontomerkosA, KaklamanisP, et al. (1997) Family history as a risk factor for rheumatoid arthritis: a case-control study. J Rheumatol 24: 1522–1526.

56. FriesJF, WolfeF, AppleR, ErlichH, BugawanT, et al. (2002) HLA-DRB1 genotype associations in 793 white patients from a rheumatoid arthritis inception cohort: frequency, severity, and treatment bias. Arthritis Rheum 46: 2320–2329.

57. HutchinsonD, ShepstoneL, MootsR, LearJT, LynchMP (2001) Heavy cigarette smoking is strongly associated with rheumatoid arthritis (RA), particularly in patients without a family history of RA. Ann Rheum Dis 60: 223–227.

58. PapadopoulosNG, AlamanosY, VoulgariPV, EpagelisEK, TsifetakiN, et al. (2005) Does cigarette smoking influence disease expression, activity and severity in early rheumatoid arthritis patients? Clin Exp Rheumatol 23: 861–866.

59. DiazFJ, Rojas-VillarragaA, SalazarJC, Iglesias-GamarraA, MantillaRD, et al. (2011) Anti-CCP antibodies are associated with early age at onset in patients with rheumatoid arthritis. Joint, Bone, Spine: Revue du Rhumatisme 78: 175–178.

60. CostenbaderKH, FeskanichD, MandlLA, KarlsonEW (2006) Smoking intensity, duration, and cessation, and the risk of rheumatoid arthritis in women. Am J Med 119: 503.e501–509.

61. StoltP, BengtssonC, NordmarkB, LindbladS, LundbergI, et al. (2003) Quantification of the influence of cigarette smoking on rheumatoid arthritis: results from a population based case-control study, using incident cases. Ann Rheum Dis 62: 835–841.

62. KarlsonEW, MandlLA, HankinsonSE, GrodsteinF (2004) Do breast-feeding and other reproductive factors influence future risk of rheumatoid arthritis? Results from the Nurses' Health Study. Arthritis Rheum 50: 3458–3467.

63. GuthrieKA, DugowsonCE, VoigtLF, KoepsellTD, NelsonJL (2010) Does pregnancy provide vaccine-like protection against rheumatoid arthritis? Arthritis Rheum 62: 1842–1848.

64. SpectorTD, HochbergMC (1990) The protective effect of the oral contraceptive pill on rheumatoid arthritis: an overview of the analytic epidemiological studies using meta-analysis. J Clin Epidemiol 43: 1221–1230.

65. ScottIC, SteerS, LewisCM, CopeAP (2011) Precipitating and perpetuating factors of rheumatoid arthritis immunopathology: linking the triad of genetic predisposition, environmental risk factors and autoimmunity to disease pathogenesis. Best Pract Res Clin Rheumatol 25: 447–468.

66. PedersenM, JacobsenS, KlarlundM, PedersenBV, WiikA, et al. (2006) Environmental risk factors differ between rheumatoid arthritis with and without auto-antibodies against cyclic citrullinated peptides. Arthritis Res Ther 8: R133.

Štítky
Genetika Reprodukčná medicína

Článok vyšiel v časopise

PLOS Genetics


2013 Číslo 9
Najčítanejšie tento týždeň
Najčítanejšie v tomto čísle
Kurzy

Zvýšte si kvalifikáciu online z pohodlia domova

Aktuální možnosti diagnostiky a léčby litiáz
nový kurz
Autori: MUDr. Tomáš Ürge, PhD.

Všetky kurzy
Prihlásenie
Zabudnuté heslo

Zadajte e-mailovú adresu, s ktorou ste vytvárali účet. Budú Vám na ňu zasielané informácie k nastaveniu nového hesla.

Prihlásenie

Nemáte účet?  Registrujte sa

#ADS_BOTTOM_SCRIPTS#