# Baseline characteristics of the TRANSLATE2 cohort: a prospective study on rheumatoid arthritis-associated interstitial lung disease

Pierre-Antoine Juge, Marie-Pierre Revel, Valérie Devauchelle-Pensec, Christophe Richez, Jérôme Avouac, Lidwine Wémeau-Stervinou, René-Marc Flipo, Hilario Nunes, Nathalie Saidenberg-Kermanac'H, Jacques-Eric Gottenberg, et al.

► To cite this version:

Pierre-Antoine Juge, Marie-Pierre Revel, Valérie Devauchelle-Pensec, Christophe Richez, Jérôme Avouac, et al. Baseline characteristics of the TRANSLATE2 cohort: a prospective study on rheumatoid arthritis-associated interstitial lung disease. Joint Bone Spine, 2025, 17, pp.105991-105991. 10.1016/j.jbspin.2025.105991. hal-05346021

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Journal Pre-proof

Baseline Characteristics of the TRANSLATE2 Cohort: a Prospective
Study on Rheumatoid Arthritis-associated Interstitial Lung Disease

Pierre-Antoine Juge Marie-Pierre Debray Valérie Devauchelle
Pensec Christophe Richez Jérôme Avouac Lidwine Wemeau
Stervinou René-Marc Flipo Hilario Nunes Nathalie
Saidenberg-Kermanac'h Jacques-Eric Gottenberg Stéphane
Jouneau Arnaud Constantin Vincent Cottin Hubert Marotte Martin
Soubrier Bruno Fautrel Gaëtane Nocturne Pascal Richette Francis
Berenbaum Hagit Zylberman-Yona Isbabelle Gorenne Catherine
Bancal Raphaël Borie Esther Ebstein Marine Forien Sébastien
Ottaviani Bruno Crestani Philippe Dieudé Prof

PII: S1297-319X(25)00153-8

DOI: https://doi.org/doi:10.1016/j.jbspin.2025.105991

Reference: BONSOI 105991

To appear in: *Joint Bone Spine*

Received Date: 21 July 2025

Revised Date: 26 September 2025

Accepted Date: 6 October 2025

Please cite this article as: Juge P-Antoine, Debray M-Pierre, Pensec VD, Richez C, Avouac J, Stervinou LW, Flipo R-Marc, Nunes H, Saidenberg-Kermanac'h N, Gottenberg J-Eric, Jouneau S, Constantin A, Cottin V, Marotte H, Soubrier M, Fautrel B, Nocturne G, Richette P, Berenbaum F, Zylberman-Yona H, Gorenne I, Bancal C, Borie R, Ebstein E, Forien M, Ottaviani S, Crestani B, Dieudé P, Baseline Characteristics of the TRANSLATE2 Cohort: a Prospective Study on Rheumatoid Arthritis-associated Interstitial Lung Disease, *Joint Bone Spine* (2025), doi: https://doi.org/10.1016/j.jbspin.2025.105991

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© 2025 The Author(s). Published by Elsevier Masson SAS on behalf of Société Française de Rhumatologie.
Baseline Characteristics of the TRANSLATE2 Cohort: a Prospective Study on
Rheumatoid Arthritis-associated Interstitial Lung Disease

Pierre-Antoine Juge¹,², Marie-Pierre Debray³, Valérie Devauchelle Pensec⁴,⁵,
Christophe Richez⁶,⁷, Jérôme Avouac⁸, Lidwine Wemeau Stervinou⁹, René-Marc
Flipo¹⁰, Hilario Nunes¹¹,¹², Nathalie Saidenberg-Kermanac’h¹³, Jacques-Eric
Gottenberg¹⁴,¹⁵, Stéphane Jouneau¹⁶,¹⁷, Arnaud Constantin¹⁸,¹⁹, Vincent Cottin²⁰,²¹,
Hubert Marotte²², Martin Soubrier²³,²⁴, Bruno Fautrel²⁵,²⁶, Gaëtane Nocturne²⁷,²⁸,
Pascal Richette²⁹,³⁰, Francis Berenbaum³¹, Hagit Zylberman-Yona¹, Isbabelle
Gorenne³², Catherine Bancal³³, Raphaël Borie³⁴,³⁵, Esther Ebstein¹, Marine Forien¹,
Sébastien Ottaviani¹, Bruno Crestani³⁴,³⁵ and Philippe Dieudé¹,³⁵.

1. Service de Rhumatologie, Hôpital Bichat-Claude Bernard, AP-HP, F-75018, Paris, France.

2. Université de Paris, INSERM U-1153, Centre de recherche en épidémiologie et statistiques, Paris, France.

3. Service de Radiologie, Hôpital Bichat-Claude Bernard, AP-HP, F-75018, Paris, France.

4. Service de Rhumatologie, CHU de Brest, Brest, France.

5. INSERM 1227 LBAI Université de Bretagne Occidentale, Centre de Référence des Maladies Auto-Immunes Rares de l'Adulte, Brest, France.

6. Service de Rhumatologie, Centre de référence des maladies auto-immunes systémiques rares RESO, Hôpital Pellegrin, Bordeaux, France.

7. ImmunoConcEpT, CNRS UMR 5164, Université de Bordeaux, Bordeaux, France.

8. Service de Rhumatologie, Hôpital Cochin - Assistance Publique Hôpitaux de Paris - Université Paris Cité, Paris, France.

9. Centre de Référence constitutif des maladies pulmonaires rares, CHRU, Lille, France

10. Service de Rhumatologie, Hôpital Salengro, Centre Hospitalier Universitaire Lille, Université de Lille, France.

11. Service de Pneumologie, site constitutif du Centre de Référence des Maladies Pulmonaires Rares, Hôpital Avicenne, Assistance Publique Hôpitaux de Paris, Bobigny.

12. Inserm UMR U1272, Université Sorbonne Paris Nord, Bobigny, France.

13. Service de Rhumatologie, Hôpital Avicenne, Assistance Publique Hôpitaux de Paris, Bobigny.

14. Service de rhumatologie, Centre national de référence des maladies autoimmunes et systémiques rares (CNR RESO), Hôpital de Hautepierre, Strasbourg, France.

15. Laboratoire d'immunopathologie et de chimie thérapeutique, institut de biologie moléculaire et cellulaire (IBMC), CNRS UPR3572, Strasbourg, France
16. Service de Pneumologie, Centre de Compétences pour Les Maladies Pulmonaires Rares, CHU de Rennes, Rennes, France.

17. IRSET UMR108, Univ Rennes, Rennes, France.

18. Service de Rhumatologie, Hôpital Pierre-Paul Riquet, CHU Purpan, Toulouse, France.

19. INFINITY, INSERM UMR 1291, CHU Purpan, Toulouse, France.

20. Service de pneumologie, Hospices Civils de Lyon, Hôpital Louis Pradel, Centre de référence coordonnateur des maladies pulmonaires rares (OrphaLung), Lyon, France.

21. Université Lyon 1, INRAE, UMR754, Lyon, France.

22. Université Jean Monnet Saint-Étienne, CHU Saint-Étienne, Service de Rhumatologie, Mines Saint-Etienne, INSERM, SAINBIOSE U1059, F-42023 Saint-Etienne, France.

23. Service de Rhumatologie, CHU Clermont-Ferrand, Clermont-Ferrand, France.

24. Université Clermont-Auvergne, INRAE, UNH, Clermont-Ferrand, France.

25. Service de Rhumatologie, AP-HP, Pitié-Salpêtrière Hospital, Paris, France.

26. CEREMAIA Reference Center (ERN RITA), Sorbonne Université, Paris, France.

27. Service de Rhumatologie, Hôpital du Kremlin-Bicêtre, Le Kremlin-Bicêtre, Île-de-France, France.

28. Université Paris-Sud, INSERM U1184: Centre for Immunology of Viral Infections and Autoimmune Diseases, Le Kremlin-Bicêtre, France.

29. Service de Rhumatologie, AP-HP, Hôpital Lariboisière, Fédération de Rhumatologie, Paris, France.

30. Inserm UMR-S 1132, Université Paris Cité, Paris, France.

31. Service de Rhumatologie, Sorbonne Université, INSERM CRSA, AP-HP Hôpital Saint-Antoine, Paris, France.

32. Service d'Epidémiologie, Biostatistique et de Recherche Clinique, Hôpital Bichat, AP-HP, Paris, France.

33. Service de Physiologie et d'Explorations Fonctionelles, Hôpital Bichat-Claude Bernard, AP-HP, F-75018, Paris, France.

34. Service de Pneumologie, Allergologie et Transplantation, AP-HP, Hôpital Bichat, Centre de Référence Constitutif des Maladies Pulmonaires Rares, Paris, France.

35. Université de Paris, INSERM UMR 1152, F-75018, Paris, France.

**Corresponding author:**

Prof. Philippe Dieudé

Service de Rhumatologie, Hôpital Bichat

Address: 46 rue Henri Huchard

Paris, France - 75018

E-mail: philippe.dieude@aphp.fr
**Manuscript word count:** 2845/3600

**Number of Tables and Figures:** 5 (4 tables and 1 figure)/6

**References:** 25/40

## Highlights

* TRANSLATE2 investigates rheumatoid arthritis associated interstitial lung disease.

* This national prospective cohort included 275 cases and 231 controls.

* It is a deeply phenotyped dataset including DNA, RNA and serum biobanking.

## ABSTRACT

**Objectives.** To describe the baseline characteristics of patients enrolled in the TRANSLATE2 cohort (NCT04227535), a national, multicenter, prospective case-control study designed to investigate the genetic and non-genetic determinants of interstitial lung disease (ILD) in rheumatoid arthritis (RA).

**Methods.** Cases with RA-ILD and RA controls without ILD were consecutively included in TRANSLATE2 with a 5-year prospective follow-up. All participants fulfilled the ACR/EULAR 2010 classification criteria for RA. ILD presence or absence was confirmed for every participant by chest high-resolution computed tomography (HRCT). Baseline demographic and clinical data were collected. Blood samples were collected at enrollment for centralized biobanking of DNA, RNA, and serum to support future genetic and biomarker studies. For ILD cases, chest HRCT scans were centrally reviewed to determine HRCT pattern. For the current study, associations with ILD were tested using univariable and multivariable logistic regression models.

**Results.** Among the 506 patients included (275 RA-ILD, 231 RA-noILD), RA-ILD cases were more frequently male (48.4% vs. 29.9%), older at enrollment (66.6 [9.9] vs. 58.5 [13.2] years) and older at RA onset (52.2 [14.7] vs. 45.8 [14.3] years). ILD was independently associated with male sex (OR 1.82; 95% CI 1.06, 3.14) and older age at RA onset (OR per 10 years 1.28; 95% CI 1.10,1.50). For ILD cases, the most frequent HRCT patterns were definite for usual interstitial pneumonia (39.3%) and non-specific interstitial pneumonia (17.8%). At enrollment, respiratory symptoms were observed in 67.3% with a mean forced vital capacity % predicted of 87.6% (21.7) and a mean diffusing capacity of the lung for carbon monoxide % predicted of 58.4% (18.8).
**Conclusion.** The TRANSLATE2 cohort provides a comprehensive and deeply phenotyped dataset that offers a unique opportunity to investigate the genetic architecture, risk factors, and natural history of RA-ILD.

287/300 words

**Key words:** Rheumatoid arthritis, interstitial lung disease, cohort
# 1. Introduction

Rheumatoid Arthritis (RA) is a systemic autoimmune rheumatic disease affecting approximately 0.5% of the general population. (1) RA can be associated with several extra-articular manifestations including interstitial lung disease (ILD). (2) RA-ILD is a heterogeneous condition encompassing different subtypes of fibrosing and non-fibrosing ILDs such as usual interstitial pneumonia [UIP], non-specific interstitial pneumonia [NSIP], and organizing pneumonia [OP]...). (3) The natural history of RA-ILD also varies between patients with ILD progression observed in half of cases. (4) Over the past decades, advances in imaging, especially chest high-resolution computed tomography (HRCT) scan, have significantly improved RA-ILD diagnosis, shedding light on an underestimated prevalence. If about 10% of the patients with RA will develop clinical ILD, a systematic screening by chest HRCT can identify subclinical ILD in 20-30%. (5-7) Significant progress in unravelling RA-ILD has followed, including the identification of several risk factors.

According to current understanding, RA-ILD is a multifactorial disease resulting from different genetic and non-genetic risk factors. (8) Part of RA-ILD genetic architecture has been uncovered through candidate-gene approaches, focusing on loci of interest implicated in other forms of ILDs. This includes the *MUC5B* promoter common variant rs35705950, the strongest genetic factor for idiopathic pulmonary fibrosis (IPF) and the first one to be validated for RA-ILD. (9) *MUC5B* rs35705950 T minor allele is associated with an approximately threefold increased risk of developing ILD in RA. Interestingly, this risk is restricted to the *UIP* pattern which is shared with IPF. Following *MUC5B* rs35705950, association between RA-ILD and other IPF-associated common variants such as *TOLLIP* rs5743890, *IVD* rs2034650, or *DSP* rs2076295 have been reported without definitive
validation. (9-11) RA-ILD also shares some similar genetic risk factors with familial
pulmonary fibrosis (FPF) with the identification in cases with RA-ILD of an excess of
rare variants located in several genes that have been previously linked to FPF. (12)
For now, the identification of specific (i.e., not overlapping with other ILDs) genetic
risk factors for ILD in RA has been limited. To date, the only genome-wide
association study in RA-ILD has been performed in a Japanese population, resulting
in the identification of an association between RA-ILD and a common variant, *RPA3-
UMAD1* rs12702634, that failed replication in European populations. (13, 14) Efforts
to decipher the genetic architecture of RA-ILD through untargeted approaches have
been largely constrained by the absence of dedicated cohorts combining chest HRCT
validated pulmonary phenotypes and sufficient sample sizes to detect common
variants having a small effect.

In order to facilitate genetic investigation in RA-ILD, identify other risk factors
for RA-ILD and better characterize natural history of RA-ILD, the Deciphering
Rheumatoid Arthritis-associated Interstitial Lung Disease Pathogenesis 2
(TRANSLATE2) has enrolled cases and controls from 2020 to 2023. This study aims
to describe the baseline characteristics of the 506 patients enrolled in TRANSLATE2.

## 2. Methods

### 2.1 Objectives and design of the TRANSLATE2 cohort

TRANSLATE2 cohort is a national multicentered case-control study
consecutively enrolling cases with RA-ILD and controls with RA without ILD with a 5-
years prospective annual follow-up (NCT04227535,
https://clinicaltrials.gov/study/NCT04227535). The primary objective is to identify
genetic risk factors for ILD in RA. Secondary objectives include identification of non-genetic risk factors for ILD in RA, characterization of RA-ILD natural history with the identification of genetic and non-genetic prognostic factors.

The design of the study has been elaborated by a scientific committee including expert rheumatologists, pulmonologists, radiologists, geneticists, and statisticians. Patients were recruited from rheumatology or pulmonary departments over 17 distinct French tertiary centers: Hôpital Bichat Claude Bernard, Hôpital Cochin, Hôpital Lariboisière, Hôpital St Antoine, and Hôpital de La Pitié Salpêtrière, Paris, Hôpital Calmette and Hôpital Roger Salengro, Lille, Hôpital Purpan, Toulouse, Centre Hospitalier Universitaire de St Etienne, St Etienne, Centre Hospitalier Universitaire de Gabriel-Montpied, Clermont-Ferrand, Hôpital Pontchaillou, Rennes, Hôpital Avicenne, Bobigny, Centre Hospitalier Universitaire La Cavalle Blanche, Brest, Hôpital Hautepierre, Strasbourg, Hôpital Bicêtre, Le Kremlin Bicêtre, Hôpital Pellegrin, Bordeaux, and Hôpital Louis Pradel, Lyon.

## 2.2 Ethics

This study is fulfilling the current Good Clinical Practice Guidelines and has obtained the approval of an ethical committee (Comité de Protection des Personnes Nord Ouest III, 19.02.27.62129). All participants at the study gave their written informed consent.

## 2.3 Population

Patients were eligible for enrolment if they were at least 18 years old, met the ACR/EULAR 2010 classification criteria for RA (15) and had either HRCT-confirmed ILD for cases or a chest HRCT showing no interstitial abnormalities within 6 months prior to enrollment for controls. Cases were considered as prevalent when the first
chest HRCT scan demonstrating ILD had been performed at least 6 months before
enrollment, and as incident if ILD was diagnosed on a chest HRCT scan performed
within 6 months prior to enrollment or during follow-up. For incident cases diagnosed
at enrollment, we did not anticipate a prior chest HRCT showing no ILD. For each
patient, a senior rheumatologist validated RA diagnosis and a senior pulmonologist
or radiologist validated the presence or absence of ILD on a chest HRCT scan. All
patients provided written informed consent prior to the inclusion. Patients were
consecutively enrolled to respect a final 1:1 ratio between cases and controls. No
matching per center were required.

## 2.4 Clinical and biological data collection

We collected the following data on a case record form at enrollment (baseline)
and at each annual visit (except for demographics, familial medical history, or RA and
ILD data prior to enrollment that were only collected at baseline), **table 1**. Biological
data were assessed locally as part of routine patient care.

* Demographics: age, sex, self-reported ethnicity;

* Body mass index (BMI);

* Personal history of secondary Sjögren disease (sSD), including anti-SSA antibody status, and cancer;

* Tobacco smoking status (never, current, past) and level (pack-year), and professional exposure associated with increased risk of ILD;

* RA characteristics: age at disease onset, anti-citrullinated peptides antibodies (ACPA) and rheumatoid factor (RF) positivity and titers (crude and normalized to the upper limit of normal, ULN), erosive status;
* RA clinical activity: 28-tender joint count (TJC) and 28-swollen joint count (SJC), visual analogue scale (VAS) score of the patient's global health, and c-reactive protein level to calculate the 28-joint disease activity score (DAS28);

* ILD characteristics: date of ILD diagnosis (defined as the date of the first chest HRCT scan showing ILD), presence and date of onset of respiratory symptoms;

* History of RA and ILD specific treatments prior to enrollment;

* Hemoglobin level, mean corpuscular volume (MCV), and platelet count;

* Pulmonary function test results including forced vital capacity (FVC), forced expiratory volume (FEV1), total lung capacity (TLC), residual volume (RV) and diffusing capacity of the lung for carbon monoxide (DLCO).

## 2.5 Chest HRCT review

For each RA-ILD case, an expert radiologist (MPD) will centrally review three chest HRCT scan imaging (baseline, 2^nd^ or 3^rd^, and 5^th^ year of follow-up). For each chest HRCT, the ILD pattern will be determined according to the 2018 ATS/ERS/JRS/ALAT guidelines, (16) ILD extent will be visually estimated, (17) and presence of other HRCT findings including bronchiolitis, non-traction bronchiectasis, hilar or mediastinal lymph nodes, and pleural effusion will be collected. For prevalent cases, we also retrospectively collected the HRCT pattern at ILD diagnosis as notified by the radiologist on the clinical review. For RA controls without ILD, HRCT scans were locally reviewed by a senior radiologist to confirm absence of ILD.

## 2.6 Biobanking
Blood was drawn for cases and controls at enrollment and centrally collected at the Biological Resource Center at Hôpital Bichat for DNA, messenger RNA and serum biobanking.

## 2.7 Statistical analyses

For the current study, baseline characteristics will be described using mean (standard deviation, SD) or median (interquartile range, IQR) for continuous variables and number (percentage) for categorical variables. The association between variables and ILD in RA was tested in a univariable logistic regression and a multivariable logistic regression model. Because time-varying variables may reflect differences in the timing of enrollment between cases and controls (i.e., any time after RA-ILD diagnosis for RA-ILD cases vs. a minimum of 6 month after a clinically indicated chest HRCT for RA controls without ILD) and because RA treatment strategies is influenced by the presence of ILD, we excluded these variables from the multivariable analysis. All other variables that showed a significant association in the univariate analyses were included in the multivariable model. We did not perform imputation for missing data and the model included individuals without missing covariates. Statistical analyses were performed using R 4.4.1. Statistical level of significance was defined as two-sided p<0.05.

# 3. Results

## 3.1 Flow chart of the study

Between February 2020 to May 2023, 511 patients were included. Five patients were excluded from the baseline analysis (3 without RA and 2 duplicate inclusions), resulting in a total of 506 patients included in the final cohort. As of May
2025, 419 patients were still participating in the study and 17 had completed the 5-year follow-up, while 70 had withdrawn early: 50 deaths during follow-up (including 41 cases), 4 consent withdrawals, and 16 lost to follow-up. Flow chart of the study is shown in **figure 1**. Each center included between 5 and 256 patients (median 15).

## 3.2 Patient characteristics

A total of 506 patients, 304 female (60.1), mean age at enrolment 62.9 years (12.2) were included in the TRANSLATE2 cohort. Characteristics of the patients are available in **table 2**. As of March 2025, 275/506 (54.3) were included as cases and 231 as controls (45.7).

The univariate analyses showed that cases with RA-ILD were more frequently male (OR 2.20; 95% CI 1.53, 3.19), more likely to be ever smokers (OR 1.57; 95% CI 1.10, 2.24), had higher cumulative smoking exposure (OR per 10 pack-years 1.14; 95% CI 1.04, 1.25), and more likely to be reported with a personal history of cancer (OR 2.30; 95% CI 1.25, 4.42), **table 3**. Lung and gynecological cancers were the more frequent, both reported in 14 patients: 11 cases and 3 controls for lung cancers, and 9 cases and 5 controls for gynecological cancers. RA-ILD cases were older at RA onset (OR per 10 years 1.35; 95% CI 1.19, 1.54), had higher ACPA and RF titers (OR per 10 times the ULN 1.09; 95% CI 1.01, 1.13 and median RF normalized titers (OR per 10 times the ULN 1.15; 95% CI 1.03, 1.29), and had lower RA disease activity at enrollment (OR per unit 0.81; 95% CI 0.71, 0.93), though similar CRP level (OR per 10 mg/L 1.04 (0.97, 1.14). As expected, cases and controls differed in term of RA treatments. At enrollment, RA-ILD cases were less likely to be currently treated by methotrexate (MTX, OR 0.59; 95% CI 0.34, 0.994), TNF inhibitors (TNFi, OR 0.60; 95% CI 0.41, 0.87) and JAK inhibitors (JAKi, OR 0.53; 95% CI 0.29, 0.92) and more likely to be currently treated by rituximab (RTX, OR 1.92; 95% CI 1.28, 2.92).
In a multivariable model including sex, smoking status, age at RA onset, ACPA and RF titers, an independent association was observed between ILD and male sex (OR 1.82; 95% CI 1.06, 3.14) and older age at RA onset (OR per 10 years 1.28; 95% CI 1.10,1.50), **table 3**.

Among RA-ILD cases, 219/275 had a prevalent ILD (80.8) and mean ILD duration at enrolment was 5.2 years (5.9), **table 4**. Respiratory symptoms (i.e., clinical ILD) were present in 181 patients (65.8). At enrollment, 124 ILD cases (45.1) had a UIP pattern including case with definite or probable UIP. NSIP was observed in 49 cases (17.8). A minimal ILD without definite HRCT pattern was observed in 51 (18.5) cases. Overall, 142 cases (51.6%) had a fibrosing ILD. At enrollment, mean FVC, FVC % predicted (FVCpp) and DLCO % predicted (DLCOpp) were 2.74 L (0.99), 87.6 (21.7), and 58.4 (18.8), respectively. Impaired FVCpp, defined as < 80%, was observed in 89/243 (36.6) cases and impaired DLCOpp, defined as <75%, was observed in 183/225 (81.3) cases. In contrast, 36/235 (15.3) cases had normal FVCpp and DLCOpp. Among the 94 cases without respiratory symptoms at enrollment, 60 (63.8) had an altered FVCpp and/or DLCOpp. As of May 2025, 41/275 (14.9) cases with ILD had died during follow-up.

**4. Discussion**

The TRANSLATE2 cohort is the first large-scale, prospective, multicenter case-control study dedicated to RA-ILD. Encompassing over 500 widely phenotyped patients, this study integrates DNA, RNA, and serum biobanking, centralized interpretation of chest HRCT scans, and a longitudinal 5-year follow-up.
In this study, we reported the baseline characteristics of cases and controls enrolled in the TRANSLATE2 cohort, which are consistent with previously described clinical profiles of patients with RA, with or without ILD. The presence of ILD was independently associated with male sex and older age at RA onset which are two established RA-ILD risk factors. (5) If high autoantibody titers and tobacco smoking were associated with RA-ILD in univariable analyses, the association failed to reach statistical significance in the multivariable model. (18-21) The power to detect independent associations may have been limited by the high prevalence of seropositivity and ever smoking among both cases and controls in our cohort. Moreover, the relationship between these factors and RA-ILD has been inconsistently reported in the literature, highlighting the need for further studies to draw any final conclusion on their role in RA-ILD pathogenesis.

Several other variables differed between cases and controls. First, a personal history of cancer was more frequently observed in cases with RA-ILD. Although an increased incidence of cancer, including lung cancer, has been reported in RA-ILD, (22) our finding may result from the older age, higher prevalence of tobacco use, and greater burden of comorbidities among RA-ILD patients. The relationship between RA-ILD and cancer incidence in the TRANSLATE2 cohort warrants further investigation using appropriate statistical models. Second, though CRP level did not differ according to ILD status, RA controls without ILD had higher DAS28 scores at enrollment. Although increased RA disease activity has been reported in patients with RA-ILD, (23) our finding is probably explained by the requirement of a recent clinically indicated chest HRCT for inclusion in TRANSLATE2. If for cases with ILD chest HRCT scan are frequently performed for ILD follow-up, for controls, chest HRCT scans may have been part of a pre-treatment evaluation before initiating
targeted DMARDs in patients with active RA. An extensive retrospective collection of RA activity before enrolment in TRANSLATE2 is therefore needed to better estimate its impact on ILD occurrence. Lastly, there were significant differences in DMARDs use at enrollment between cases and controls. Although national and international recommendations for RA treatment in patients with RA-ILD have now been published, (24, 25) no guidelines were available at the time of enrollment in TRANSLATE2, particularly regarding the use of DMARDs, the presence of ILD would be expected to influence the prescription of DMARDs in patients with RA. In agreement with a previous study performed in the French National Healthcare Data System, RA cases with ILD were more frequently treated by RTX and received less frequently MTX (26). Additionally, RA-ILD cases were less frequently treated with JAKi, likely due to their clinical profiles (i.e., being older, more often male and more frequently smokers). A dedicated analysis of RA treatment trajectories prior to ILD diagnosis within the TRANSLATE2 cohort may presents a valuable opportunity to investigate the potential impact of DMARDs on ILD development in RA.

The ILD characteristics observed in cases within the TRANSLATE2 cohort reflect the heterogeneity of RA-ILD. The distribution of symptomatic and asymptomatic ILD cases (67.3% and 34.2%, respectively) provides an opportunity for distinct investigation. Stratified analyses according to HRCT pattern or the presence of fibrosis will also be feasible. In TRANSLATE2, as expected in RA-ILD, the predominant HRCT pattern was UIP, followed by NSIP. (27) A significant group of patients with minimal ILD not meeting the criteria for a specific HRCT pattern was also included. With the growing detection of limited ILD through clinically indicated chest HRCT scans, prospective investigation of this emerging subgroup will be particularly informative. At enrollment, lung function was impaired (i.e., low FVCpp
and/or DLCOpp) for most of the cases with ILD, even in patients without any respiratory symptoms. The 5-year prospective follow-up, including clinical, functional, and radiological assessments of ILD in cases, will enable the description of the natural course of both limited and extensive RA-ILD. It will also provide a great opportunity to confirm and identify new risk factors for ILD progression, which is a current unmet need in RA-ILD. Although the 5-year follow-up is still ongoing for the majority of patients, a substantial number of deaths have already been observed among those with ILD, underscoring the severity of RA-ILD. Through dedicated analyses, TRANSLATE2 will enable an updated assessment of the ILD burden in RA, including the identification of risk factors associated with mortality.

Although TRANSLATE2 does not reflect the natural frequency of RA-ILD, being enriched for ILD cases due to its 1:1 case-control design, this approach was chosen to align with our primary objective (i.e., the investigation of RA-ILD genetic architecture). Compared with other existing RA-ILD cohorts, the large sample size including both cases and controls confirmed to be free of ILD by HRCT, and the 5-years prospective follow-up will provide substantial strength to our cohort. (28, 29) With this design, TRANSLATE2 offers 80% power to detect a minimum allele frequency difference of 6% to 12% for variants with a minor allele frequency ranging from 5% to 50% in controls.

Altogether, TRANSLATE2 represents a comprehensive and novel dataset that offers a unique and powerful resource to deepen our understanding of the genetic architecture of RA-ILD, unravel its pathogenic mechanisms, and define its natural course. Beyond its primary objectives, we anticipate that the clinical and biological data collected through TRANSLATE2 will support ancillary studies aimed at further enhancing the understanding and management of RA-ILD.
**Disclosure of interest**

The authors declare that they have no conflict of interest concerning this study.

**Acknowledgment**

The TRANSLATE2 cohort study was sponsored by Assistance Publique – Hôpitaux de Paris through the Clinical Research Unit Paris Nord Secteur Ouest and endorsed by the French Society of Rheumatology. Funding was provided by Bristol Myers Squibb (BMS). BMS was not involved in the study design, data collection, analyses or interpretation, and does not have access to the data.
References

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<table><caption>Table 1. TRANSLATE2 data collection over the 5-year follow-up.</caption><thead><tr><th>Study visit</th><th>Enrollment</th><th>1-year follow-up</th><th>2-year follow-up</th><th>3-year follow-up</th><th>4-year follow-up</th><th>5-year follow-up</th></tr></thead><tbody><tr><td>Clinical</td><td><ul><li>Demographics</li><li>BMI</li><li>Personal and Familial medical history</li><li>Tobacco and professional exposure</li><li>RA characteristics</li><li>DAS28-CRP</li><li>RA prior and current treatment</li><li>ILD characteristics</li><li>ILD prior and current treatment</li></ul></td><td><ul><li>BMI</li><li>Tobacco exposure</li><li>RA characteristics</li><li>RA current treatment</li><li>DAS28-CRP</li><li>ILD characteristics</li><li>ILD current treatment</li></ul></td><td><ul><li>BMI</li><li>Tobacco exposure</li><li>RA characteristics</li><li>RA current treatment</li><li>DAS28-CRP</li><li>ILD characteristics</li><li>ILD current treatment</li></ul></td><td><ul><li>BMI</li><li>Tobacco exposure</li><li>RA characteristics</li><li>RA current treatment</li><li>DAS28-CRP</li><li>ILD characteristics</li><li>ILD current treatment</li></ul></td><td><ul><li>BMI</li><li>Tobacco exposure</li><li>RA characteristics</li><li>RA current treatment</li><li>DAS28-CRP</li><li>ILD characteristics</li><li>ILD current treatment</li></ul></td><td><ul><li>BMI</li><li>Tobacco exposure</li><li>RA characteristics</li><li>RA current treatment</li><li>DAS28-CRP</li><li>ILD characteristics</li><li>ILD current treatment</li></ul></td></tr><tr><td>Biological*</td><td><ul><li>CBC</li><li>CRP-level</li><li>RF, ACPA, anti-SSA</li><li>DNA</li><li>RNA</li><li>Serum</li></ul></td><td><ul><li>CBC</li><li>CRP-level</li></ul></td><td><ul><li>CBC</li><li>CRP-level</li></ul></td><td><ul><li>CBC</li><li>CRP-level</li></ul></td><td><ul><li>CBC</li><li>CRP-level</li></ul></td><td><ul><li>CBC</li><li>CRP-level</li></ul></td></tr><tr><td>Other</td><td><ul><li>PFTs at diagnosis and enrollment</li><li>HRCT at diagnosis and enrollment**</li></ul></td><td><ul><li>PFTs</li><li>HRCT if performed**</li></ul></td><td><ul><li>PFTs</li><li>HRCT**</li></ul></td><td><ul><li>PFTs</li><li>HRCT**</li></ul></td><td><ul><li>PFTs</li><li>HRCT if performed**</li></ul></td><td><ul><li>PFTs</li><li>HRCT**</li></ul></td></tr></tbody></table>

Data in italics are only collected in cases with ILD.

*DNA, RNA and serum samples will be systematically collected at enrollment for cases and controls who have provided consent. Additional biological data will be collected as part of the routine clinical care for patients with RA.

**For cases, a central review of images will be performed for chest HRCT scans at 3 different time points (enrollment, 2 or 3-year follow-up, and 5-year follow-up). If additional chest HRCT scans are performed, data from clinical reviews be collected.

ACPA: anti-citrullinated peptides antibodies; BMI: body mass index; CBC: complete blood count; CRP: c-reactive protein; DAS28: 28-joint disease activity score; HRCT: high-resolution computed tomography; ILD: interstitial lung disease; PFT: pulmonary function test; RA: rheumatoid arthritis; RF: rheumatoid factor.
<table><caption>Table 2. Baseline characteristics of the 506 patients included in TRANSLATE2.</caption><thead><tr><th></th><th>Overall<br>n=506</th><th>RA-ILD<br>cases<br>n=275</th><th>RA-noILD<br>controls<br>N=231</th></tr></thead><tbody><tr><td><strong>Demographics</strong></td><td></td><td></td><td></td></tr><tr><td>Female, n (%)</td><td>304 (60.1)</td><td>142 (51.6)</td><td>162 (70.1)</td></tr><tr><td>Age, years (SD)</td><td>62.9 (12.2)</td><td>66.6 (9.9)</td><td>58.5 (13.2)</td></tr><tr><td>Ethnicity, n (%)</td><td></td><td></td><td></td></tr><tr><td>- European</td><td>312 (62.7)</td><td>167 (62.3)</td><td>145 (63.0)</td></tr><tr><td>- North African</td><td>85 (17.1)</td><td>42 (15.7)</td><td>43 (18.7)</td></tr><tr><td>- Sub-Saharan African</td><td>41 (8.2)</td><td>31 (11.6)</td><td>10 (4.3)</td></tr><tr><td>- Asian</td><td>22 (4.4)</td><td>11 (4.1)</td><td>11 (4.8)</td></tr><tr><td>- Caribbean</td><td>18 (3.6)</td><td>9 (3.4)</td><td>9 (3.9)</td></tr><tr><td>- Mixed/Other</td><td>16 (3.2)</td><td>6 (2.2)</td><td>10 (4.3)</td></tr><tr><td>BMI, kg/m² (IQR)</td><td>27.1 (5.2)</td><td>27.4 (5.2)</td><td>26.7 (5.1)</td></tr><tr><td>Tobacco smoking status, n (%)</td><td></td><td></td><td></td></tr><tr><td>- Current</td><td>70 (13.9)</td><td>34 (12.4)</td><td>36 (15.7)</td></tr><tr><td>- Past</td><td>208 (41.3)</td><td>131 (47.8)</td><td>77 (33.5)</td></tr><tr><td>- Never</td><td>226 (44.8)</td><td>109 (39.8)</td><td>117 (50.9)</td></tr><tr><td>Tobacco smoking level, pack-year<br>(IQR)</td><td>3.0 (0.0, 25.0)</td><td>9.0 (0.0, 30.0)</td><td>0.0 (0.0, 18.0)</td></tr><tr><td><strong>Comorbidities</strong></td><td></td><td></td><td></td></tr><tr><td>Personal history, n (%)</td><td></td><td></td><td></td></tr><tr><td>- Cancer</td><td>53 (10.5)</td><td>38 (13.9)</td><td>15 (6.6)</td></tr><tr><td>- Sjogren disease</td><td>70 (13.9)</td><td>39 (14.3)</td><td>31 (13.4)</td></tr><tr><td><strong>RA characteristics</strong></td><td></td><td></td><td></td></tr><tr><td>Age at RA onset, year (SD)</td><td>49.3 (14.8)</td><td>52.2 (14.7)</td><td>45.8 (14.3)</td></tr><tr><td>RA duration, year (SD)</td><td>3.4 (2.9)</td><td>3.6 (2.8)</td><td>2.9 (2.6)</td></tr><tr><td>ACPA</td><td></td><td></td><td></td></tr><tr><td>- positive, n (%)</td><td>430 (86.7)</td><td>234 (87.0)</td><td>196 (86.3)</td></tr><tr><td>- titer, normalized (IQR)</td><td>17.4 (2.9, 34.1)</td><td>21.4 (3.2, 34.1)</td><td>13.1 (2.7, 34.1)</td></tr><tr><td>RF</td><td></td><td></td><td></td></tr><tr><td>- positive, n (%)</td><td>381 (76.8)</td><td>213 (79.8)</td><td>168 (73.4)</td></tr><tr><td>- titer, normalized (IQR)</td><td>4.8 (0.0, 20.1)</td><td>5.8 (1.2, 28.3)</td><td>4.2 (0.0, 14.4)</td></tr><tr><td>Seropositive, n (%)</td><td>452 (89.3)</td><td>244 (88.7)</td><td>208 (90.0)</td></tr><tr><td>SSA/Ro antibody positive, n (%)</td><td>38 (8.9)</td><td>20 (8.9)</td><td>18 (8.9)</td></tr><tr><td>Erosive, n (%)</td><td>314 (65.4)</td><td>165 (64.7)</td><td>149 (66.2)</td></tr><tr><td>DAS28-CRP, unit (SD)</td><td>3.2 (1.4)</td><td>3.0 (1.4)</td><td>3.4 (1.4)</td></tr><tr><td>CRP, mg/L (SD)</td><td>11.3 (25.3)</td><td>12.4 (29.9)</td><td>10.1 (18.7)</td></tr><tr><td><strong>Current RA treatment</strong></td><td></td><td></td><td></td></tr><tr><td>MTX, n (%)</td><td>305 (60.4)</td><td>156 (56.9)</td><td>149 (64.5)</td></tr><tr><td>Other csDMARDs, n (%)</td><td>20 (4.0)</td><td>12 (4.4)</td><td>8 (3.5)</td></tr><tr><td>Any b/tsDMARD, n (%)</td><td>268 (53.3)</td><td>143 (52.6)</td><td>125 (54.1)</td></tr><tr><td>TNFi, n (%)</td><td>70 (13.9)</td><td>30 (11.0)</td><td>40 (17.3)</td></tr><tr><td>Abatacept, n (%)</td><td>55 (11.0)</td><td>34 (12.5)</td><td>21 (9.1)</td></tr><tr><td>IL6i, n (%)</td><td>37 (7.4)</td><td>16 (5.9)</td><td>21 (9.1)</td></tr><tr><td>RTX, n (%)</td><td>68 (13.5)</td><td>51 (18.7)</td><td>17 (7.4)</td></tr><tr><td>JAKi, n (%)</td><td>38 (7.6)</td><td>12 (4.4)</td><td>26 (11.3)</td></tr><tr><td>Current oral steroids, n (%),<br>Current oral steroids dose, eq. pred.<br>mg (SD)</td><td>279 (55.4)<br>3.8 (5.7)</td><td>153 (55.8)<br>4.0 (6.6)</td><td>126 (54.8)<br>3.6 (4.5)</td></tr></tbody></table>

ACPA: anti-citrullinated peptides antibodies; cs/b/tsDMARD: conventional/biologic/targeted synthetic disease-modifying anti-rheumatic drug; BMI: body mass index; CRP: c-reactive protein; DAS28: 28-joint disease activity score; eq. pred.: equivalent prednisone; IL6i: interleukine-6 inhibitor; ILD: interstitial lung disease; MTX: methotrexate; RA: rheumatoid arthritis; RF: rheumatoid factor; RTX: rituximab; TNFi: TNF inhibitors; JAKi: Janus kinase inhibitors.
<table><caption>Table 3. Univariate and multivariate analyses testing association with RA-ILD.</caption><thead><tr><th></th><th>Univariable analyses<br>OR (95% CI)</th><th>Multivariable model<br>OR (95%CI)</th></tr></thead><tbody><tr><td><strong>Demographics</strong></td><td></td><td></td></tr><tr><td>Male sex (vs. female)</td><td>2.20 (1.53, 3.19)</td><td>1.82 (1.06, 3.14)</td></tr><tr><td>European (vs. non-European)</td><td>0.92 (0.64, 1.31)</td><td></td></tr><tr><td>BMI, (per kg/m²)</td><td>1.02 (0.99, 1.06)</td><td></td></tr><tr><td>Ever smokers (vs. never)</td><td>1.57 (1.10, 2.24)</td><td>1.19 (0.71, 1.96)</td></tr><tr><td>Tobacco smoking level (per 10 pack-years)</td><td>1.14 (1.04, 1.25)</td><td></td></tr><tr><td><strong>Comorbidities</strong></td><td></td><td></td></tr><tr><td>Personal history</td><td></td><td></td></tr><tr><td>- Cancer (yes vs. no)</td><td>2.30 (1.25, 4.42)</td><td></td></tr><tr><td>- Sjogren disease (yes vs. no)</td><td>1.08 (0.65, 1.80)</td><td></td></tr><tr><td><strong>RA characteristics</strong></td><td></td><td></td></tr><tr><td>Age at RA onset (per 10 years)</td><td>1.35 (1.19, 1.54)</td><td>1.28 (1.10, 1.50)</td></tr><tr><td>RA duration (per year)</td><td>1.06 (0.99, 1.13)</td><td></td></tr><tr><td>ACPA</td><td></td><td></td></tr><tr><td>- positive (yes vs. no)</td><td>1.06 (0.63, 1.78)</td><td></td></tr><tr><td>- titer (per 10 times the ULN)</td><td>1.09 (1.01, 1.20)</td><td>1.07 (0.998, 1.20)</td></tr><tr><td>RF</td><td></td><td></td></tr><tr><td>- positive, (yes vs. no)</td><td>1.43 (0.94, 2.18)</td><td></td></tr><tr><td>- titer (per 10 times the ULN)</td><td>1.15 (1.03, 1.29)</td><td>1.11 (0.96, 1.28)</td></tr><tr><td>SSA positive (yes vs. no)</td><td>1.00 (0.51, 1.97)</td><td></td></tr><tr><td>Erosive (yes vs. no)</td><td>0.94 (0.64, 1.36)</td><td></td></tr><tr><td>DAS28-CRP (per unit)</td><td>0.81 (0.71, 0.93)</td><td></td></tr><tr><td>CRP (per 10 mg/L)</td><td>1.04 (0.97, 1.14)</td><td></td></tr><tr><td><strong>RA treatment*</strong></td><td></td><td></td></tr><tr><td>MTX</td><td>0.59 (0.34, 0.994)</td><td></td></tr><tr><td>Other csDMARDs</td><td>0.94 (0.61, 1.46)</td><td></td></tr><tr><td>Any b/tsDMARD</td><td>0.94 (0.66, 1.34)</td><td></td></tr><tr><td>TNFi</td><td>0.60 (0.41, 0.87)</td><td></td></tr><tr><td>Abatacept</td><td>1.41 (0.90, 2.24)</td><td></td></tr><tr><td>IL6i</td><td>0.88 (0.53, 1.45)</td><td></td></tr><tr><td>RTX</td><td>1.92 (1.28, 2.92)</td><td></td></tr><tr><td>JAKi</td><td>0.53 (0.29, 0.92)</td><td></td></tr><tr><td>Current oral steroids</td><td>1.04 (0.73, 1.49)</td><td></td></tr><tr><td>Current oral steroids dose (per mg)</td><td>1.01 (0.98, 1.04)</td><td></td></tr></tbody></table>

ACPA: anti-citrullinated peptides antibodies; cs/b/tsDMARD: biologic or targeted synthetic disease-modifying anti-rheumatic drug; BMI: body mass index; CRP: c-reactive protein; DAS28: 28-joint disease activity score; eq. pred.: equivalent prednisone; IL6i: interleukine-6 inhibitor; ILD: interstitial lung disease; MTX: methotrexate; RA: rheumatoid arthritis; RF: rheumatoid factor; RTX: rituximab; TNFi: TNF inhibitors; JAKi: Janus kinase inhibitors.

<footnote>*ever treated vs. never if not indicated</footnote>
<table><caption>Table 4. ILD characteristics for cases at inclusion in Translate2.</caption><thead><tr><th></th><th>RA-ILD cases<br>n=275</th></tr></thead><tbody><tr><td><strong>ILD characteristics</strong></td><td></td></tr><tr><td>Age at ILD diagnosis, year (SD)</td><td>61.5 (11.5)</td></tr><tr><td>Prevalent ILD, n (%)</td><td>219 (80.8)</td></tr><tr><td>ILD duration, year (SD)</td><td>5.2 (5.9)</td></tr><tr><td>Respiratory symptoms, n (%)</td><td>181 (65.8)</td></tr><tr><td>HRCT pattern, n (%)</td><td></td></tr><tr><td>- UIP definite</td><td>108 (39.3)</td></tr><tr><td>- UIP probable</td><td>16 (5.8)</td></tr><tr><td>- NSIP</td><td>49 (17.8)</td></tr><tr><td>- NSIP/OP</td><td>1 (0.4)</td></tr><tr><td>- Minimal ILD</td><td>51 (18.5)</td></tr><tr><td>- Other/unclassifiable</td><td>50 (18.2)</td></tr><tr><td>Fibrosing ILD, n (%)</td><td>142 (51.6)</td></tr><tr><td><strong>PFTs</strong></td><td></td></tr><tr><td>FVC, L (SD)</td><td>2.74 (0.99)</td></tr><tr><td>FVCpp, % (SD)</td><td>87.6 (21.7)</td></tr><tr><td>DLCOpp, % (SD)</td><td>58.4 (18.8)</td></tr><tr><td><strong>Current ILD treatment</strong></td><td></td></tr><tr><td>Anti-fibrotic, n (%)</td><td>29 (10.7)</td></tr><tr><td>Long-term oxygen use, n (%)</td><td>16 (5.9)</td></tr></tbody></table>

DLCOpp: diffusing capacity of the lung for carbon monoxide % predicted; FVC: forced vital capacity; FVCpp: forced vital capacity % predicted; HRCT: high-resolution computed tomography; ILD: interstitial lung disease; NSIP: non-specific interstitial pneumonia; OP: organizing pneumonia; PFT: pulmonary function test; RA: rheumatoid arthritis; UIP: usual interstitial pneumonia.
<caption>Figure 1. Flowchart of the TRANSLATE2 cohort.</caption>

ILD: interstitial lung disease; RA: rheumatoid arthritis.

<figure><img src="image_3.png" /></figure>