Environmental exposures and biomarkers predictive of rheumatoid arthritis and the pathway to precision medicine

Environmental exposures and biomarkers predictive of rheumatoid arthritis and the pathway to precision medicine

Sasha M. Bernatsky1, Jean C. Pfau2, Marvin J. Fritzler3

1Research Institute of the McGill University Health Centre, McGill University, Montreal, Quebec, Canada; 2Department of Microbiology and Immunology, Montana State University, Bozeman, MT, USA; 3Cumming School of Medicine, University of Calgary, Calgary, Canada

Correspondence to: Marvin J. Fritzler, PhD, MD. Cumming School of Medicine, University of Calgary, 3330 Hospital Dr. NW, Calgary, AB, T2N 4N1, Canada. Email: fritzler@ucalgary.ca.

Provenance: This is a Guest Editorial commissioned by the Section Editor Zaixing Yang (Department of Laboratory Medicine, Taizhou First People’s Hospital, Taizhou, China).

Comment on: van Zanten A, Arends S, Roozendaal C, et al. Presence of anticitrullinated protein antibodies in a large population-based cohort from the Netherlands. Ann Rheum Dis 2017. [Epub ahead of print].

Received: 07 February 2017; Accepted: 08 February 2017; Published: 21 February 2017.

doi: 10.21037/jlpm.2017.02.01

Rheumatoid arthritis (RA) is regarded as a systemic autoimmune rheumatic disease (SARD) where the major clinical manifestations involve symmetrical arthrodial joints and are associated with increased direct and indirect health care costs (1). Few of the other SARD (i.e., systemic lupus erythematosus (SLE), systemic sclerosis, autoimmune inflammatory myopathies) have been the benefactors of the tremendous progress in understanding RA disease onset, pathogenesis, diagnostic approaches, and therapeutic options (1,2). Indeed, related to this progress, there are emerging efforts to identify at risk individuals (3-6), arrive at an early and accurate diagnosis of “pre-RA” and then initiate evidence-based disease interventions (7,8). Implicit in the approach to disease prevention is the need for precision medical approaches such as the ‘systems biology based P4 model’ (Predictive, Preventive, Personalized, Participatory) espoused by Flores et al. (9) and others.

A key to the P4 approach is an understanding of elements that predate the development of clinically obvious RA. Certainly, dating to the 1970s, there is a fulsome literature on the biomarkers that attend the diagnosis of RA. These include genomic markers such as HLA-DBRB1 and the so-called shared epitope (10), epigenetic markers such as modifications of chromatin (i.e., methylation and acetylation) (10-12), autoantibodies that historically include rheumatoid factor, but more recently focused on autoantibodies directed to citrullinated peptides (ACPA), as well as cytokines and interleukins such as Il-1, IL-15 and IL-17 (13).

If they are to be used to ‘predict’ RA and enter a medical management pathway of precision medicine, it is imperative that there is a thorough understanding of how these biomarkers are represented in unselected populations. In this light, a recent study by van Zanten et al. from the Netherlands provides important insight into the clinical utility of ACPA through a population-based study of >40,000 individuals that are part of a larger prospective “Lifelines” study in their country (www.Lifelines.net) (14).

In RA, environmental factors appear to play a more significant role than genetic factors and may be the ‘second hit’ that is needed to convert an individual into the RA disease trajectory. The rather small influence of genetic factors in RA is exemplified by the concordance rate of RA in monozygotic twins of approximately 14% and only 4% in dizygotic twins [reviewed in (15)]. Of the environmental factors implicated in RA, periodontitis and cigarette smoking are best established as risk factors for the disease [reviewed in (14)] and emerging evidence has implicated air pollution and other routes of exposure (16,17) in the form of silica (16,18), traffic emissions (19,20) and particulates (21) as significant co-factors. Other risk factors implicated in RA include occupation (17,22,23), obesity (24), socioeconomic (22), dietary carbohydrates (25), seasonal effects (26), pesticides (17), and alcohol may actually be protective (27). Other factors (physical and psychological trauma, surgery, infections) have also been reported but are poorly substantiated [reviewed in (26,28)].

In the benchmark study of van Zanten et al. (14), the link of ACPA to self-reported disease that could be taken as either established or pre-RA was the focus, and many of the factors referred to above were addressed. It is important to appreciate that this study utilized an adjusted cut-off for ACPA because, as the authors explain, the ACPA cut-offs appropriate for a healthy population are not clearly established. Since they desired “to use the test to detect ACPA and not as a diagnostic test for RA”, a 99-centile cut-off value of ≥6.2 U/mL was chosen, whereas the manufacturer’s cut-off value for RA diagnostics was recommended to be ≥10 U/mL. Using this cut-off for the non-RA group, older age, smoking and joint complaints remained significantly more frequently present in ACPA-positive compared with ACPA-negative participants. For example, in this unselected population study 1.0% had ACPA levels that were higher than an adjusted cutoff. Notably, a positive ACPA was significantly associated with older age, female sex, smoking, joint complaints, RA and first degree relatives (FDR) with rheumatism. Further, in the Lifelines study, of the ACPA-positive participants, 22.4% had RA (15.2% with defined RA and 7.2% self-reported RA only). However, in participants without RA, 0.8% were ACPA-positive. When the manufacturer’s recommended cutoff of ≥10 U/mL was used, ACPA-positive participants reported significantly less use of sugar-sweetened soft drinks, and women were less often nulliparous. Other previously-reported risk factors for RA and ACPA were not significantly associated with ACPA positivity. For example, body mass index (BMI) and being overweight were previously associated with RA (24) but in this study BMI was not associated with ACPA positivity. In addition, an association with alcohol non-use and ACPA positivity and/or higher ACPA titers, self-reported periodontitis, dietary fish intake as a protective factor or sugar-sweetened soft drinks as an aggravating factor for RA was not detected.

Despite the valuable insight that this remarkable study provides, the possible geographic clustering of disease and potential or observed exposure to pollution were not reported. This is of importance because if RA is to be prevented or mitigated, remediation of environmental factors should be one of the major considerations.

While ACPA-positivity is clearly an important marker for early detection of RA, the Lifelines study confirms other studies demonstrating that a significant subset of RA patients is ACPA-negative. One potentially helpful model of RA etiology proposes that environmental triggers of RA should be defined in categories. Within this model emerges the possibility that different sets of triggers drive ACPA-positive vs. ACPA-negative RA. In this case, the Lifelines database and cohort may provide an invaluable tool for testing this hypothesis. For example, there is evidence that cigarette smoking is associated with an increased risk of ACPA-positive RA, but not ACPA-negative RA, and cigarette smoking in the context of the HLA-DRB1 genetic background is associated with a high-risk for ACPA-positive RA [reviewed (29)]. The discovery that smoking increases expression of enzymes associated with protein citrullination, which could trigger development of ACPA, led to further studies to identify environmental RA triggers that were (or were not) associated with ACPA. Although not apparent in the Lifelines study (14), in other recent studies periodontitis linked to Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans has been associated with ACPA-positive RA, and significant protein citrullination (30,31). However, RA associated with inhalation exposures to silica or asbestos tend to be ACPA-negative in the absence of smoking, despite the ability of silica nanoparticles to increase citrullination in lung cells [reviewed (32)]. An association between RA and exposure to crystalline silica (quartz) has become well established, and more recently asbestos has also been reported as a trigger for RA (33). The mechanism whereby these silicate mineral dust exposures drive RA may be different than environmental triggers that lead to ACPA-positive RA (32), and likely a SARD-permissive genetic environment will be necessary for full disease development.

Ambient air pollution and other occupational exposures, as possible triggers for the development of SARD, has been the focus of other studies. Notable industrial emissions include fine particulate matter (PM2.5) and sulfur dioxide (SO2). Most particulate matter is formed from gases emitted from power plants, industries and automobiles motor vehicles, although some particulate matter is directly emitted from smokestacks and other sources. Industrial activities are the largest sources of SO2 emissions followed by combustion of fossil fuels at power plants and other emissions from motor vehicles and industrial facilities. Since particulate matter may trigger a host of non-rheumatologic health problems (34) it would be intriguing to confirm whether some components of air pollution trigger rheumatic disease encompassing RA as well. Links between PM2.5 levels and SLE activity have been reported (35), as well as evidence supporting an increased risk of certain SARD with PM2.5 (36). Analysis of death certificates in 26 USA states concluded that death from SARD were associated with occupational exposures encountered in farming and industry (23) and analysis of data extracted from the Nurses’ Health Study found an association between exposure to traffic pollution and RA suggesting that pollution from traffic in adulthood may be a newly identified environmental risk factor for RA (19). Studies of a Swedish cohort reported that exposure to NO2, but not particulate matter, was associated with RA risk (22). One study reported that measures of air pollution levels were associated with a 60% increased risk of juvenile idiopathic arthritis in young children (21). However, other studies did not find any clear links between RA onset and traffic-related NO2 levels or regional PM2.5 levels (20). As mentioned earlier, there is convincing evidence that tobacco smoking may induce ACPA but to date no publications have clearly linked air pollution and ACPA.

In conclusion, the application of precision medicine to the prediction and effective intervention leading to prevention of RA is still in its early stages. The factors described above implicated as triggers for onset and perpetuation of RA provide an approach that may help to detect environmental triggers for RA and to better understand gene/environment interactions in RA. Many other environmental triggers may still be identified. In some instances, variability in research approaches and discordant results strongly suggest that additional, thorough, coordinated research efforts are required in the future. Variability in measurement of air pollution, both in terms of types and timing, may in part explain the inconsistencies in these reports. In addition, it is well known that no one environmental or xenobiotic factor alone induces SARD; multiple genes appear to be susceptible to xenobiotic-induced epigenetic modifications leading to a SARD-permissive state where multiple exposures (i.e., second and third “hits”) are likely required to trigger RA. Therefore, the development and progression of RA may depend on synergistic effects of environmental factors such as air pollution, cigarette smoking, and infections on a susceptible genetic background. A fulsome understanding of these factors is important on a clinical care pathway for RA that embraces precision medicine.




Conflicts of Interest: MJ Fritzler is a consultant to and/or has received honoraria or gifts in kind from Inova Diagnostics Inc. (San Diego, CA, USA), Werfen International (Barcelona, Spain), and Euroimmun GmbH (Luebeck, Germany). The other authors have no conflicts of interest to declare.


  1. Malmström V, Catrina AI, Klareskog L. The immunopathogenesis of seropositive rheumatoid arthritis: from triggering to targeting. Nat Rev Immunol 2017;17:60-75. [Crossref] [PubMed]
  2. Jutley G, Raza K, Buckley CD. New pathogenic insights into rheumatoid arthritis. Curr Opin Rheumatol 2015;27:249-55. [Crossref] [PubMed]
  3. Li J, Tseng KK, Hsieh ZY, et al. Staining pattern classification of antinuclear autoantibodies based on block segmentation in indirect immunofluorescence images. PLoS One 2014;9:e113132. [Crossref] [PubMed]
  4. van Nies JA, Krabben A, Schoones JW, et al. What is the evidence for the presence of a therapeutic window of opportunity in rheumatoid arthritis? A systematic literature review. Ann Rheum Dis 2014;73:861-70. [Crossref] [PubMed]
  5. Mankia K, Emery P. A new window of opportunity in rheumatoid arthritis: targeting at-risk individuals. Curr Opin Rheumatol 2016;28:260-6. [Crossref] [PubMed]
  6. Brekelmans MP, Fens N, Brinkman P, et al. Smelling the Diagnosis: The Electronic Nose as Diagnostic Tool in Inflammatory Arthritis. A Case-Reference Study. PLoS One 2016;11:e0151715. [Crossref] [PubMed]
  7. Arend WP, Firestein GS. Pre-rheumatoid arthritis: predisposition and transition to clinical synovitis. Nat Rev Rheumatol 2012;8:573-86. [Crossref] [PubMed]
  8. Law SC, Benham H, Reid HH, et al. Identification of self-antigen-specific T cells reflecting loss of tolerance in autoimmune disease underpins preventative immunotherapeutic strategies in rheumatoid arthritis. Rheum Dis Clin North Am 2014;40:735-52. [Crossref] [PubMed]
  9. Flores M, Glusman G, Brogaard K, et al. P4 medicine: how systems medicine will transform the healthcare sector and society. Per Med 2013;10:565-76. [Crossref] [PubMed]
  10. Sparks JA, Costenbader KH. Genetics, environment, and gene-environment interactions in the development of systemic rheumatic diseases. Rheum Dis Clin North Am 2014;40:637-57. [Crossref] [PubMed]
  11. Araki Y, Mimura T. The Mechanisms Underlying Chronic Inflammation in Rheumatoid Arthritis from the Perspective of the Epigenetic Landscape. J Immunol Res 2016;2016:6290682.
  12. Angiolilli C, Baeten DL, Radstake TR, et al. The acetyl code in rheumatoid arthritis and other rheumatic diseases. Epigenomics 2017. [Epub ahead of print]. [Crossref] [PubMed]
  13. Sharma J, Bhar S, Devi CS. A review on interleukins: The key manipulators in rheumatoid arthritis. Mod Rheumatol 2017.1-24. [Crossref] [PubMed]
  14. van Zanten A, Arends S, Roozendaal C, et al. Presence of anticitrullinated protein antibodies in a large population-based cohort from the Netherlands. Ann Rheum Dis 2017. [Epub ahead of print]. [Crossref] [PubMed]
  15. Gan L, O'Hanlon TP, Gordon AS, et al. Twins discordant for myositis and systemic lupus erythematosus show markedly enriched autoantibodies in the affected twin supporting environmental influences in pathogenesis. BMC Musculoskelet Disord 2014;15:67. [Crossref] [PubMed]
  16. Parks CG, Conrad K, Cooper GS. Occupational exposure to crystalline silica and autoimmune disease. Environ Health Perspect 1999;107 Suppl 5:793-802. [Crossref] [PubMed]
  17. Cooper GS, Miller FW, Germolec DR. Occupational exposures and autoimmune diseases. Int Immunopharmacol 2002;2:303-13. [Crossref] [PubMed]
  18. Stolt P, Yahya A, Bengtsson C, et al. Silica exposure among male current smokers is associated with a high risk of developing ACPA-positive rheumatoid arthritis. Ann Rheum Dis 2010;69:1072-6. [Crossref] [PubMed]
  19. Hart JE, Laden F, Puett RC, et al. Exposure to traffic pollution and increased risk of rheumatoid arthritis. Environ Health Perspect 2009;117:1065-9. [Crossref] [PubMed]
  20. De Roos AJ, Koehoorn M, Tamburic L, et al. Proximity to traffic, ambient air pollution, and community noise in relation to incident rheumatoid arthritis. Environ Health Perspect 2014;122:1075-80. [Crossref] [PubMed]
  21. Zeft AS, Prahalad S, Schneider R, et al. Systemic onset juvenile idiopathic arthritis and exposure to fine particulate air pollution. Clin Exp Rheumatol 2016;34:946-52. [PubMed]
  22. Li X, Sundquist J, Sundquist K. Socioeconomic and occupational risk factors for rheumatoid arthritis: a nationwide study based on hospitalizations in Sweden. J Rheumatol 2008;35:986-91. [PubMed]
  23. Gold LS, Ward MH, Dosemeci M, et al. Systemic autoimmune disease mortality and occupational exposures. Arthritis Rheum 2007;56:3189-201. [Crossref] [PubMed]
  24. Versini M, Jeandel PY, Rosenthal E, et al. Obesity in autoimmune diseases: not a passive bystander. Autoimmun Rev 2014;13:981-1000. [Crossref] [PubMed]
  25. Hu Y, Costenbader KH, Gao X, et al. Sugar-sweetened soda consumption and risk of developing rheumatoid arthritis in women. Am J Clin Nutr 2014;100:959-67. [Crossref] [PubMed]
  26. Söderlin MK, Bergsten U, Svensson B, et al. Patient-reported events preceding the onset of rheumatoid arthritis: possible clues to aetiology. Musculoskeletal Care 2011;9:25-31. [Crossref] [PubMed]
  27. Scott IC, Tan R, Stahl D, et al. The protective effect of alcohol on developing rheumatoid arthritis: a systematic review and meta-analysis. Rheumatology (Oxford) 2013;52:856-67. [Crossref] [PubMed]
  28. Sakkas LI, Bogdanos DP. Infections as a cause of autoimmune rheumatic diseases. Auto Immun Highlights 2016;7:13. [Crossref] [PubMed]
  29. Scott IC, Seegobin SD, Steer S, et al. Predicting the risk of rheumatoid arthritis and its age of onset through modelling genetic risk variants with smoking. PLoS Genet 2013;9:e1003808. [Crossref] [PubMed]
  30. de Smit MJ, Westra J, Brouwer E, et al. Periodontitis and Rheumatoid Arthritis: What Do We Know? J Periodontol 2015;86:1013-9. [Crossref] [PubMed]
  31. Konig MF, Abusleme L, Reinholdt J, et al. Aggregatibacter actinomycetemcomitans-induced hypercitrullination links periodontal infection to autoimmunity in rheumatoid arthritis. Sci Transl Med 2016;8:369ra176. [Crossref] [PubMed]
  32. Pfau JC. Rheumatoid Arthrtis. In: Dietert RR, Luebke RW. editors. Immunotoxicity, Immune Dysfunction, and Chronic Disease. New York: Humana Press, 2012:171-92.
  33. Pfau JC, Serve KM, Noonan CW. Autoimmunity and asbestos exposure. Autoimmune Dis 2014;2014:782045.
  34. Bernatsky S, Smargiassi A, Barnabe C, et al. Fine particulate air pollution and systemic autoimmune rheumatic disease in two Canadian provinces. Environ Res 2016;146:85-91. [Crossref] [PubMed]
  35. Bernatsky S, Fournier M, Pineau CA, et al. Associations between ambient fine particulate levels and disease activity in patients with systemic lupus erythematosus (SLE). Environ Health Perspect 2011;119:45-9. [Crossref] [PubMed]
  36. Bernatsky S, Smargiassi A, Johnson M, et al. Fine particulate air pollution, nitrogen dioxide, and systemic autoimmune rheumatic disease in Calgary, Alberta. Environ Res 2015;140:474-8. [Crossref] [PubMed]
doi: 10.21037/jlpm.2017.02.01
Cite this article as: Bernatsky SM, Pfau JC, Fritzler MJ. Environmental exposures and biomarkers predictive of rheumatoid arthritis and the pathway to precision medicine. J Lab Precis Med 2017;2:5.