Article Text

Short peripheral blood leukocyte telomere length in rheumatoid arthritis-interstitial lung disease
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  1. Tracy J Doyle1,
  2. Pierre-Antoine Juge2,3,
  3. Anna L Peljto4,
  4. Seoyeon Lee4,
  5. Avram D Walts5,
  6. Anthony Joseph Esposito1,6,
  7. Sergio Poli1,
  8. Ritu Gill7,
  9. Hiroto Hatabu8,
  10. Mizuki Nishino8,
  11. Paul F Dellaripa9,
  12. Michael E Weinblatt9,
  13. Nancy A Shadick9,
  14. M Kristen Demoruelle10,
  15. Jeffrey A Sparks9,
  16. Ivan O Rosas11,
  17. Benjamin Granger12,
  18. Kevin D Deane10,
  19. Bruno Crestani2,13,
  20. Paul J Wolters14,
  21. Philippe Dieudé2,3,
  22. Joyce S Lee14
  1. 1 Department of Medicine, Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
  2. 2 Université Paris Cité, INSERM UMR 1152, F-75018, Paris, France
  3. 3 Service de Rhumatologie, Hôpital Bichat-Claude Bernard, AP-HP, F-75018, Paris, France
  4. 4 Department of Medicine, Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California San Francisco, San Francisco, California, USA
  5. 5 Department of Medicine, National Jewish Health, Denver, Colorado, USA
  6. 6 Department of Medicine, Division of Pulmonary and Critical Care Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
  7. 7 Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
  8. 8 Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts, USA
  9. 9 Department of Medicine, Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Boston, Massachusetts, USA
  10. 10 Department of Medicine, Division of Rheumatology, University of Colorado School of Medicine, Aurora, Colorado, USA
  11. 11 Department of Medicine, Division of Pulmonary and Critical Care Medicine, Baylor College of Medicine, Houston, Texas, USA
  12. 12 Sorbonne Université, INSERM, Institut Pierre Louis d’Epidémiologie et de Santé Publique (IPLESP), Hôpital Pitié Salpétrière, Public Health Department, F75013, Paris, France
  13. 13 Department of Pulmonology, Centre de Référence des Maladies Pulmonaires Rares, Hopital Bichat-Claude Bernard, APHP, Paris, France
  14. 14 Department of Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado School of Medicine, Denver, Colorado, USA
  1. Correspondence to Dr Tracy J Doyle, Department of Medicine, Brigham and Women's Hospital, Boston, MA 02132, USA; tjdoyle{at}bwh.harvard.edu

Abstract

Shortened telomere lengths (TLs) can be caused by single nucleotide polymorphisms and loss-of-function mutations in telomere-related genes (TRG), as well as ageing and lifestyle factors such as smoking. Our objective was to determine if shortened TL is associated with interstitial lung disease (ILD) in individuals with rheumatoid arthritis (RA). This is the largest study to demonstrate and replicate that shortened peripheral blood leukocytes-TL is associated with ILD in patients with RA compared with RA without ILD in a multinational cohort, and short PBL-TL was associated with baseline disease severity in RA-ILD as measured by forced vital capacity percent predicted.

  • rheumatoid lung disease
  • interstitial fibrosis

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Introduction

Telomere shortening has been associated with interstitial lung disease (ILD),1 in particular idiopathic pulmonary fibrosis (IPF)2 and autoimmune conditions such as rheumatoid arthritis (RA).3 Clinically-evident ILD is present in 10% of RA individuals in a predominantly usual interstitial pneumonia (UIP) pattern,4 and telomerase mutations have been found in 12% of RA-ILD patients.5 RA-ILD has been associated with shorter peripheral blood leucocyte (PBL)-TL when compared with non-RA connective tissue disease-ILD in one study demonstrating an association between short telomeres and prevalent ILD, as well as in another study among RA patients in a single cohort.6 7 We sought to determine if shortened PBL-TL is associated with ILD in individuals with RA and with RA-ILD disease severity at inclusion.

Methods

Subjects

This case-control study of RA with ILD (RA-ILD) and without ILD (RA-noILD) included derivation (FRENCH RA-ILD network) and replication groups (University of California San Francisco, Brigham and Women’s Hospital, University of Colorado Denver). TLs were measured using a quantitative PCR (qPCR) assay of DNA isolated from PBLs as previously described.8 The institutional review boards at each institution approved all protocols, and all patients provided written informed consent. See online supplemental materials for additional details regarding diagnostic criteria, data and blood sample collection, TL measurement, and composition of each group.

Supplemental material

Statistical analysis

This case-control study compared RA-ILD to RA-noILD. A multivariable logistic regression model assessing the association between PBL-TL and ILD status was developed in the derivation group and tested in the replication group. As sensitivity analyses, a multivariable logistic regression model was developed using stepwise regression to select covariates based on the Akaike information criterion, and the multivariable model was tested in subjects age 45–75 to try to account for any residual confounding by age. Among subjects with RA-ILD, unadjusted and adjusted regression models were used to assess the strength of the association between PBL-TL, as a predictor variable, and forced vital capacity percent predicted (FVC%), diffusion capacity of lung for carbon monoxide percent predicted (DLCO%), or probable or definite UIP chest HRCT pattern as dependent variables in the combined groups. Linear regression models were used for the continuous dependent variables, FVC% and DLCO%, while logistic regression was used for the binary UIP dependent variable (probable or definite compared with none). See online supplemental materials for additional details regarding statistical methods.

Results

The derivation group included 205 RA-noILD and 150 RA-ILD subjects. The replication group included 86 RA-noILD and 109 RA-ILD subjects. In the derivation group, RA-ILD subjects, were older at time of blood draw, more frequently male, older at age of RA onset, had longer RA duration compared with RA-noILD and were more likely to have used methotrexate and/or rituximab (table 1). In the replication group, RA-ILD subjects were older at time of blood draw, older at age of RA onset, and less likely to have used methotrexate (table 1).

Table 1

Baseline characteristics of the derivation, replication and pooled groups

The absolute PBL-TLs were shorter in RA-ILD compared with RA-noILD in the derivation, replication, and pooled study groups (table 1). Telomere length and age for RA-noILD and RA-ILD with their respective fitted values are presented in figure 1.

Figure 1

Telomere length and age for RA-noILD (○) and RA-ILD (●) in the pooled group with their respective fitted lines.

In a multivariable logistic regression model adjusted for variables based on biological rationale and on univariate association with RA-ILD in the derivation group (p<0.10) (online supplemental table 1), the association between short PBL-TL and RA-ILD diagnosis persisted when adjusted for age, sex, ever smoking, RA duration, and ever methotrexate use; OR 0.39, 95%CI 0.25 to 0.60, p<0.001 in the derivation group. These findings were supported in the replication group, though due to missing data, RA duration was not included in the model (OR 0.42, 95%confidence interval 0.29 to 0.62, p<0.001). (online supplemental table 1, table 2). A sensitivity analysis was performed using stepwise variable selection in the derivation group. This method demonstrated that short PBL-TL was significantly associated with RA-ILD diagnosis after adjusting for age, sex, and ever methotrexate use in the derivation group (OR 0.38, 95%confidence interval 0.25 to 0.58, p<0.001) and confirmed in the replication group (OR 0.44, 95%confidence interval 0.30 to 0.63, p<0.001) (table 2). An additional sensitivity analysis in a more age-similar sample limited to subjects ages 45–75 showed a significant effect for PBL-TL in the same direction as in the full cohort (OR 0.60, 95%confidence interval 0.41 to 0.88, p<0.009).

Table 2

Multivariable logistic regression models of ILD status among RA patients in derivation, replication and pooled groups

Among those with RA-ILD in the pooled group, PBL-TL was associated with FVC % predicted (at closest proximity to blood draw) on unadjusted analyses and when adjusted for age at blood draw, male sex and ever smoking (β 4.88, 95%confidence interval 1.45 to 8.31, p=0.01) (online supplemental table 2). There was no association between PBL-TL and DLCO % predicted or probable/definite UIP pattern on HRCT. A sensitivity analysis excluding those with a PFT>6 months from PBL-TL measurement did not impact our primary findings (online supplemental results and online supplemental table 3). Time between RA diagnosis, ILD diagnosis, PBL-TL measurement, and PFTs in the pooled group is provided in online supplemental table 4.

Discussion

To our knowledge, this is the largest study to demonstrate and replicate that shortened PBL-TL is associated with ILD status among patients with RA across a multinational cohort. In addition, this study is the first to demonstrate that, in patients with RA-ILD, short PBL-TL was associated with baseline disease severity as measured by FVC%, although not with DLCO% nor the UIP HRCT sub-phenotype.

Individuals with other ILDs and shortened TL and/or telomerase mutations have been shown to have more rapid progression,6 shorter transplant-free survival,9 and worse transplant-related outcomes.10 It will be important to determine if RA-ILD individuals with short PBL-TL have similarly poor outcomes, as measurement of PBL-TL could be an important tool in guiding treatment decisions.

Our study has the following limitations: (1) Although a multinational study, our group was mainly non-Hispanic white, limiting generalizability to other races. (2) There are inherent limitations in the qPCR method of measuring PBL-TL. However, measurement of TL using a common method and replication of the findings in separate groups suggest that these did not impact the results. (3) Missing/unavailable data, including pack-years of smoking, and different methods of obtaining co-variate data across the groups may have introduced bias and/or limited some of our analyses. However, the findings remained consistent across different statistical methodologies. For more information regarding missing data broken down by ILD status, please see online supplemental tables 5 and 6) (4) It is possible that some of the individuals with RA-noILD may have had undiagnosed ILD, but this would bias our findings towards the null. (5) Although the regression model was constructed to limit the potential for confounding explaining the results, it is still possible the age difference may have a confounding effect. (6) Lack of clinically relevant outcomes (eg, transplant, death), for the majority of individuals has limited our ability to look at the association between PBL-TL and prognosis.

Shortened PBL-TL is associated with ILD in RA and with baseline disease severity among RA-ILD. These findings suggest that telomere shortening may contribute to the pathogenesis of RA-ILD. Future studies should investigate the relationship between PBL-TL and RA-ILD progression and patient outcomes to determine if PBL-TL could be used as a biomarker in combination with other risk factors to potentially inform screening and management decisions in this high-risk RA population.

Ethics statements

Patient consent for publication

Ethics approval

This study involves human participants and was approved by The institutional review boards at each institution approved all protocols, and all patients provided written informed consent. We are happy to provide approval numbers for all institutions or the institution doing the analysis at your request. Participants gave informed consent to participate in the study before taking part.

Acknowledgments

We offer our sincere thanks to the patients with RA who participated and to the staff of BRASS and the Arthritis Center at Brigham and Women’s Hospital for their efforts in this study.

References

Supplementary materials

  • Supplementary Data

    This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

Footnotes

  • TJD and P-AJ contributed equally.

  • PD and JSL contributed equally.

  • Contributors All listed authors made substantial contributions to the conception or design of the work (TJD, P-AJ, ALP, PFD, MEW, NAS, MKD, JAS, IOR, BG, KDD, BC, PJW, PD, JSL) or the acquisition, analysis, or interpretation of data for the work (TJD, P-AJ, ALP, SL, ADW, AJE, SF, RG, HH, MN, BG, PJW, PD, JSL), in addition to drafting the work (TJD, P-AJ, ALP, PJW, PD, JSL), or revising it critically for important intellectual content (SL, ADW, AJE, SF, RG, HH, MN, PFD, MEW, NAS, MKD, JAS, IOR, BG, KD, BC). All authors gave final approval of the version to be published and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

  • Funding This work was supported by the National Institutes of Health [K23 HL119558, R03 HL148484 and R01 HL155522 to T.J.D.; F32 HL151132 to A.J.E.; R01CA203636, 5U01CA209414, 2R01HL111024, R01HL135142, and 1R01HL130974 to HH; P30 AR079369 to KDD and MKD; R01 AR077607, P30 AR070253, and P30 AR072577 to J.A.S; K23 HL138131 to JSL]; Nina Ireland Program for Lung Health to P.J.W. BRASS is funded by grants from Bristol Myers Squibb.

  • Competing interests TJD reports grant funding and other support from Bristol Myers Squibb, Genentech, and Bayer and personal fees from Boehringer Ingelheim, unrelated to this study. PA-J reports personal fees from Bristol Myers Squibb, Boehringer Ingelheim, Astra-Zeneca and Medac unrelated to this study. MEW reports grant funding from Amgen, Bristol Myers Squibb, Eli Lilly; personal fees from Bristol Myers Squibb, Sanofi, and Eli Lilly, Abbvie, Arena Pharmaceuticals, CorEvitas, GlaxoSmithKline, Horizon Therapeutics, Pfizer, Scipher Medicine, and Setpoint Medical; and other funding from Scipher Medicine, Can-Fite Biopharma, Inmedix, and VersaPharm, unrelated to this study. NAS reports grant funding from Bristol Myers Squibb, Sanofi, Amgen, Crescendo Bioscience, Eli Lilly, and Mallinckrodt Pharmaceuticals and personal fees from Bristol Myers Squibb, unrelated to this study. RG receives grant support from Canon Medical Systems. HH reports grants from Canon Medical Systems, grants from Konica Minolta Inc, personal fees from Mitsubishi Chemical Co, personal fees from Canon Medical Systems Inc. MN reports grants from AstraZeneca, grants from Daiichi Sankyo, grants from Canon Medical Systems, grants from Merck investigator studies program, personal fees from Daiichi Sankyo, and personal fees from AstraZeneca. PFD has been a clinical investigator for Boehringer Ingelheim, Bristol Myers Squibb, and Genentech and currently works on an Advisory Committee for the FDA. JAS has received research support from Bristol Myers Squibb and performed consultancy for AbbVie, Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Gilead, Inova Diagnostics, Janssen, Optum, and Pfizer unrelated to this work. IOR reports grant funding from Genentech, unrelated to this study. KDD has received investigator-initiated grant funding from Janssen Research and Development and Pfizer, unrelated to this study; in addition, KDD reports serving as consultant for Inova Diagnostics, Inc., Bristol Myers Squibb and Exagen Diagnostics, and he has received free research assays from Inova Diagnostics, Inc., not used for this study; KDD has also received investigator-initiated grant from Janssen and Pfizer that are unrelated to this project. MKD has been the recipient of two investigator-initiated grants from Boehringer Ingelheim and Pfizer, unrelated to this research. PJW reports grants from Genentech, grants and personal fees for advisory board work from Boehringer Ingelheim and Sanofi, personal fees for advisory board work from Blade Pharmaceuticals, grants and personal fees for lectures from Pliant, outside the submitted work. JSL reports grants and other support from the NIH, Galapagos, Boehringer Ingelheim, United Therapeutics, Eleven P15, Bonac, Avalyn and the Pulmonary Fibrosis Foundation, outside the submitted work. PD reports grant funding and other support from Boehringer Ingelheim, Bristol Myers Squibb and Pfizer and personal fees from Bristol Myers Squibb, Sanofi, Lilly, Abbvie, Pfizer, Medac, Novartis, UCB Pharma and Boehringer Ingelheim, unrelated to this study. BC reports grant funding from Boehringer Ingelheim, Bristol Myers Squibb and Roche and personal fees from Astra Zeneca, Boehringer Ingelheim, Bristol Myers Squibb, CSL Behring, GSK, Novartis, Rochen and Sanofi, unrelated to this study.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.