Abstract
Objectives
The MUC5B promoter single nucleotide polymorphism (SNP) rs35705950 has been associated with idiopathic pulmonary fibrosis (IPF) and RA-related interstitial lung disease (ILD), but not with SSc-ILD. We hypothesized that the MUC5B promoter polymorphism or other IPF susceptibility loci are associated with an increased risk for the uncommon SSc-usual interstitial pneumonia (UIP) endophenotype, rather than SSc-ILD in general.
Methods
We performed a cross-sectional study of SSc-ILD patients from four US Scleroderma Programs to investigate the frequency of MUC5B rs35705950 and 12 additional IPF susceptibility loci. SSc-ILD patients were stratified by high resolution chest CT (HRCT) imaging findings into UIP and non-UIP groups. Analysis of HRCTs performed by a thoracic radiologist blinded to participants’ characteristics classified each scan as definite UIP, probable UIP, indeterminate or alternative diagnosis, according to American Thoracic Society criteria.
Results
Four-hundred and eighty-nine SSc-ILD patients were included; 80% were female and 75% were White. Twenty-three (4.7%) patients had a definite UIP pattern. The MUC5B SNP rs35705950 was not associated with a definite UIP pattern in SSc-ILD. In contrast, patients carrying two copies of the IPF risk gene FAM13A minor allele rs2609255 had significantly higher odds of a definite UIP pattern compared with the other patterns (odds ratio 3.40, 95% CI 1.19–9.70), and compared with an alternative diagnosis (odds ratio 3.65, 95% CI 1.25–10.65).
Conclusion
We demonstrated a novel association between FAM13A and SSc-UIP. Contrary to IPF and RA-ILD, the MUC5B promoter polymorphism was not associated with a definite UIP pattern in SSc-ILD.
Keywords: systemic sclerosis, interstitial lung disease, usual interstitial pneumonia, FAM13A, MUC5B
Rheumatology key messages.
FAM13A SNP rs2609255 homozygosity was associated with the usual interstitial pneumonia radiographic pattern in SSc-ILD.
MUC5B SNP rs35705950 was not associated with the usual interstitial pneumonia radiographic pattern in SSc-ILD.
The usual interstitial pneumonia radiographic pattern has a prevalence of 4.7% in patients with SSc-ILD.
Introduction
Nonspecific interstitial pneumonia (NSIP) is the most common radiographic and histopathologic pattern of interstitial lung disease (ILD) in patients with SSc. The estimated prevalence of NSIP in these patients ranges from 68% to 78% [1, 2]. In contrast, the usual interstitial pneumonia (UIP) pattern of ILD is much less commonly observed in patients with SSc-ILD, with a reported prevalence that ranges from 8% to 26% [1–4]. The UIP pattern is the hallmark of idiopathic pulmonary fibrosis (IPF) [5], and characteristic of RA-associated ILD (RA-ILD) [6]. However, the pathogenesis of these different endophenotypes of SSc-ILD is unknown.
Genetic variants, particularly in the MUC5B gene promoter, are a well-established risk factor for UIP in other types of ILD. Best recognized is a MUC5B promoter gain-of-function single nucleotide polymorphism (SNP) rs35705950 that is associated with IPF and RA-ILD, as well as with familial pulmonary fibrosis [7, 8]. However, previous studies found no association between the MUC5B rs35705950 SNP and SSc-ILD [9, 10]. Of note, overexpression of MUC5B has been found in honeycombed lung tissue from patients with IPF and RA-ILD [7, 8], but honeycombing is not a predominant feature of NSIP. Honeycombing is the hallmark of UIP, a pattern characteristic of IPF, familial pulmonary fibrosis and RA-ILD [5, 6]. In addition to MUC5B, several other genetic susceptibility loci have been identified in IPF [11–13]. We therefore hypothesized that the MUC5B promoter polymorphism, rs35705950, or one of 12 other IPF susceptibility loci, might be associated with an increased risk for the uncommon UIP endophenotype in SSc-ILD, rather than SSc-ILD in general.
Patients and methods
We performed a cross-sectional study of patients with SSc-ILD who were evaluated at one of four Scleroderma Programs in the USA: Columbia University (New York, NY, USA); Northwestern University (Chicago, IL, USA); University of California, San Francisco (San Francisco, CA, USA); and University of Texas Health Science Center at Houston (Houston, TX, USA). Participants were included if they were ≥18 years of age; met 2013 ACR/EULAR Classification Criteria for SSc [14]; had evidence of ILD on high-resolution CT (HRCT) scan of the chest; and had stored DNA. This study was approved by the Institutional Review Boards at Columbia University Irving Medical Center (#AAAS6516), Northwestern University (#STU00211957), University of California, San Francisco (#19-29270) and University of Texas Health Science Center at Houston (# HSC-MS-02-161).
All HRCT images were visually inspected by a single expert thoracic radiologist who was blinded to participants’ characteristics and was unaware of their genotypes. Images were classified according to American Thoracic Society (ATS) Criteria as definite UIP; probable UIP; indeterminate for UIP; or alternative diagnosis [5]. Based on these criteria, ‘definite UIP’ is defined as honeycombing with or without peripheral traction bronchiectasis or bronchiolectasis and has a distribution that is subpleural and basal predominant, and ‘probable UIP’ is defined as a reticular pattern with peripheral traction bronchiectasis or bronchiolectasis that may have mild ground glass opacities and has a distribution that is subpleural and basal predominant [5]. An HRCT is categorized as indeterminate for UIP when it has features of fibrosis but does not meet criteria for definite or probable UIP and the CT features do not clearly suggest an alternative diagnosis [5]. Alternative diagnosis is defined as findings suggestive of another diagnosis or has a distribution that is peribronchovascular, perilymphatic, or upper or mid lung [5]. NSIP would be included in the alternative diagnosis category.
Genotyping of the 13 investigated SNPs, selected on the basis of their replicated association with IPF and RA-ILD (Table 1) [8], was performed by TaqMan allele discrimination assays in a 7900HT fast real-time PCR system (Applied Biosystems, Foster City, CA, USA) at the University of Texas Health Science Center at Houston.
Table 1.
List of idiopathic pulmonary fibrosis susceptibility loci genotyped in this study
| SNP | Positiona | Minor allele | Locus | Nearest gene |
|---|---|---|---|---|
| rs6793295 | 169518455 | C | 3q26 | LRRC34 |
| rs2609255 | 89811195 | G | 4q22 | FAM13A |
| rs2736100 | 1286516 | A | 5p15 | TERT |
| rs7887 | 31864547 | T | 6p21.3 | EHMT2 |
| rs2076295 | 7563232 | G | 6p24 | DSP |
| rs4727443 | 99593346 | A | 7q22 | Intergenic |
| rs11191865 | 105672842 | G | 10q24 | OBFC1 |
| rs35705950 | 1241221 | T | 11p15.5 | MUC5B |
| rs5743890 | 1325829 | C | 11p15.5 | TOLLIP |
| rs111521887 | 1312706 | G | 11p15.5 | TOLLIP |
| rs1278769 | 113536627 | A | 13q34 | ATP11A |
| rs2034650 | 40717302 | G | 15q14-15 | IVD |
| rs12610495 | 4717672 | G | 19p13 | DPP9 |
Based on GRCh 37/hg19 database.
First, a logistic regression model was fit to examine the association of genotypes with the HRCT patterns, then the odds ratios (OR) and CIs were calculated from the coefficient of the model. Subsequently, the P-value was calculated based on an analysis of variance χ2 test. We also performed an a priori subgroup analysis among non-Hispanic White participants. The primary outcome was presence or absence of a definite UIP pattern on HRCT. The three genetic inheritance models—dominant, recessive and additive—were considered. For the association analysis of the demographic and clinical features with FAM13A rs2609255, we utilized χ2 and Fisher’s exact test, as appropriate, and association analyses using logistic regression when the independent variable had more than two categories.
Results
Four-hundred and eighty-nine participants were included. The median [interquartile range (IQR)] age at time of HRCT was 52 (44, 61) years. Eighty percent were female; 74.8% self-identified as non-Hispanic White, 13.7% as Black, 8.4% as Asian and 17.4% as Hispanic; the median (IQR) disease duration at time of HRCT was 4 (2, 10) years; 49.7% were classified as the diffuse cutaneous subtype; and 36.8% were positive for the anti-topoisomerase I antibody (Table 2).
Table 2.
Participant characteristics
| N = 489 | |
|---|---|
| Age at time of HRCT, median (IQR) | 52 (44, 61) |
| Female sex, n (%) | 391 (80.0) |
| Race, n (%) | |
| White | 366 (74.8) |
| Black | 67 (13.7) |
| Asian | 41 (8.4) |
| Other | 15 (3.1) |
| Hispanic ethnicity, n (%) | 85 (17.4) |
| SSc duration at time of HRCT (years), median (IQR) | 4 (2, 10) |
| Diffuse cutaneous subtype, n (%) | 243 (49.7) |
| Modified Rodnan skin score closest to HRCT, median (IQR) | 6 (3, 15) |
| N = 483 | |
| Positive ANA, n (%) | 474 (96.9) |
| N = 487 | |
| Positive anti-topoisomerase-I antibody, n (%) | 180 (36.8) |
| Positive ACA, n (%) | 40 (8.3) |
| N = 484 | |
| Positive anti-RNA polymerase 3 antibody, n (%) | 93 (21.5) |
| N = 432 | |
| FVC %predicted on PFTs closest to HRCT, median (IQR) | 72 (60, 85) |
| N = 488 | |
| DLCO %predicted on PFTs closest to HRCT, median (IQR) | 55 (41, 67) |
| N = 461 | |
| HRCT pattern, n (%) | |
| Definite UIP | 23 (4.7) |
| Probable UIP | 69 (14.1) |
| Indeterminate | 55 (11.2) |
| Alternative diagnosis | 342 (69.9) |
| Percent of lung involved on HRCT, n (%) | |
| <20% | 232 (47.4) |
| 20–50% | 195 (39.9) |
| >50% | 62 (12.7) |
DLCO: diffusion capacity for carbon monoxide; FVC: forced vital capacity; HRCT: high resolution chest CT; IQR: interquartile range; PFTs: pulmonary function tests; UIP: usual interstitial pneumonia.
The median (IQR) forced vital capacity (FVC) percent predicted on pulmonary function testing closest to HRCT was 72 (60, 85)% predicted. The median (IQR) diffusion capacity for carbon monoxide (DLCO) was 55 (41, 67)% predicted. A definite UIP pattern on HRCT was detected in 4.7% of participants, while 14.1% of subjects had probable UIP, 11.2% had an indeterminate pattern for UIP and 69.9% had an alternative diagnosis. The alternative diagnosis category was comprised mainly of NSIP and organizing pneumonia. Extent of ILD on HRCT was <20% lung involvement in 47.4% of subjects, 20–50% lung involvement in 39.9% and >50% lung involvement in 12.7% (Table 2).
We identified a statistically significant association between the FAM13A minor allele rs2609255 and definite UIP. Patients with two copies of the FAM13A minor allele had statistically significantly higher odds of a definite UIP pattern compared with the other patterns (OR 3.40, 95% CI 1.19–9.70, P-value = 0.039) and compared with an alternative diagnosis (OR 3.65, 95% CI 1.25–10.67, P-value = 0.032; Table 3). In our subgroup analysis of non-Hispanic White participants, patients with two copies of the FAM13A minor allele had higher odds of a definite UIP pattern compared with the other patterns (OR 3.81, 95% CI 0.98–14.79, P-value = 0.084) and compared with an alternative diagnosis (OR 4.43, 95% CI 0.69–19.96, P-value = 0.059; Table 3). We did not detect significant associations between any of the other IPF susceptibility loci and definite UIP (Tables 4 and 5). Of note, the MUC5B minor allele rs35705950 was not associated with a definite UIP pattern when compared with the rest of the patterns (OR 0.85, 95% CI 0.28–2.57, P-value = 0.775) or when compared with an alternative diagnosis (OR 0.85, 95% CI 0.28–2.57, P-value = 0.763; Table 3).
Table 3.
Genotypic association of FAM13A SNP rs2609255 and MUC5B SNP rs35705950 with a definite UIP pattern, in the entire cohort and among non-Hispanic White participants only
| Entire cohort | N | White participants | N | |
|---|---|---|---|---|
| Two copies of FAM13A minor allele rs2609255, n (%) | ||||
| Definite UIP | 5 (21.7) | 23 | 3 (20.0) | 15 |
| Non-definite UIP | 35 (7.6) | 463 | 17 (6.2) | 276 |
| Genotypic association test | ||||
| OR for definite UIP vs non-definite UIP (95% CI) | 3.40 (1.19–9.70) | 3.81 (0.98–14.79) | ||
| P-value | 0.039 | 0.084 | ||
| Two copies of FAM13A minor allele rs2609255, n (%) | ||||
| Definite UIP | 5 (21.7) | 23 | 3 (20.0) | 15 |
| Alternative diagnosis | 24 (7.1) | 339 | 11 (5.3) | 206 |
| Genotypic association test | ||||
| OR for definite UIP vs alternative diagnosis (95% CI) | 3.65 (1.25–10.65) | 4.43 (1.09–18.03) | ||
| P-value | 0.032 | 0.062 | ||
| Minor allele frequency of MUC5B rs35705950, n (%) | ||||
| Definite UIP | 4 (17.4) | 23 | 4 (26.7) | 15 |
| Non-definite UIP | 91 (19.8) | 460 | 67 (24.4) | 275 |
| Genotypic association test | ||||
| OR for definite UIP vs non-definite UIP (95% CI) | 0.85 (0.28–2.57) | 1.13 (0.35–3.66) | ||
| P-value | 0.775 | 0.841 | ||
| Minor allele frequency of MUC5B rs35705950, n (%) | ||||
| Definite UIP | 4 (17.4) | 23 | 4 (26.7) | 15 |
| Alternative diagnosis | 67 (19.9) | 336 | 51 (24.9) | 205 |
| Genotypic association test | ||||
| OR for definite UIP vs alternative diagnosis (95% CI) | 0.85 (0.28–2.57) | 1.10 (0.33–3.60) | ||
| P-value | 0.763 | 0.878 | ||
SNP: single nucleotide polymorphism; UIP: usual interstitial pneumonia; OR: odds ratio.
Table 4.
ORs for definite UIP vs non-definite UIP (recessive models)
| SNP | Minor allele | Nearest gene | OR (95% CI) | P-value |
|---|---|---|---|---|
| rs6793295 | C | LRRC34 | 1.51 (0.54–4.21) | 0.445 |
| rs2609255 | G | FAM13A | 3.40 (1.19–9.70) | 0.039 |
| rs2736100 | A | TERT | 1.27 (0.51–3.16) | 0.615 |
| rs7887 | T | EHMT2 | 1.09 (0.36–3.29) | 0.881 |
| rs2076295 | G | DSP | 1.72 (0.69–4.31) | 0.262 |
| rs4727443 | A | Intergenic | 0.61 (0.18–2.09) | 0.402 |
| rs11191865 | G | OBFC1 | 0.94 (0.38–2.34) | 0.900 |
| rs35705950 | T | MUC5B | 3.44 (0.40–29.82) | 0.329 |
| rs5743890 | C | TOLLIP | 2.97 (0.35–25.18) | 0.379 |
| rs111521887 | G | TOLLIP | 2.28 (0.28–18.83) | 0.488 |
| rs1278769 | A | ATP11A | 0.86 (0.11–6.67) | 0.884 |
| rs2034650 | G | IVD | 0.31 (0.07–1.34) | 0.069 |
| rs12610495 | G | DPP9 | 1.21 (0.27–5.37) | 0.810 |
UIP: usual interstitial pneumonia; OR: odds ratio.
Table 5.
ORs for definite UIP vs alternative diagnosis (recessive models)
| SNP | Minor allele |
Nearest gene | OR (95% CI) | P-value |
|---|---|---|---|---|
| rs6793295 | C | LRRC34 | 1.52 (0.54–4.28) | 0.444 |
| rs2609255 | G | FAM13A | 3.65 (1.25–10.67) | 0.032 |
| rs2736100 | A | TERT | 1.20 (0.48–3.01) | 0.700 |
| rs7887 | T | EHMT2 | 0.98 (0.32–2.99) | 0.975 |
| rs2076295 | G | DSP | 1.86 (0.73–4.71) | 0.208 |
| rs4727443 | A | Intergenic | 0.62 (0.18–2.14) | 0.425 |
| rs11191865 | G | OBFC1 | 0.98 (0.39–2.45) | 0.964 |
| rs35705950 | T | MUC5B | 3.77 (0.40–35.20) | 0.307 |
| rs5743890 | C | TOLLIP | 5.11 (0.51–51.13) | 0.230 |
| rs111521887 | G | TOLLIP | 2.15 (0.25–18.25) | 0.521 |
| rs1278769 | A | ATP11A | 0.91 (0.12–7.18) | 0.927 |
| rs2034650 | G | IVD | 0.30 (0.07–1.31) | 0.062 |
| rs12610495 | G | DPP9 | 1.19 (0.26–5.38) | 0.823 |
UIP: usual interstitial pneumonia; OR: odds ratio.
We subsequently examined participant demographic and clinical characteristics by number of FAM13A minor allele copies. Median age and proportion of females were similar between those with 0 or 1 copy of the FAM13A minor allele and those with 2 copies [age: 53 (IQR 44, 61) vs 49 (IQR 42, 59) years, respectively; female sex: 79.6% vs 82.5%, respectively; Table 6]. Asian patients were more likely than patients of other races to have two copies of the minor allele. There were no meaningful differences in SSc disease duration, SSc subtype, mRSS or autoantibody positivity based on homozygosity for minor allele FAM13A rs2609255. In addition, there were no statistically significant differences between percent predicted FVC or DLCO, or extent of ILD between those with 0 or 1 copy and those with two copies (Table 6).
Table 6.
Participant characteristics by number of FAM13A rs2609255 minor allele copies
| Total Na | 0 or 1 copy, N = 446 | 2 copies, N = 40 | P-value | |
|---|---|---|---|---|
| Age at time of HRCT, median (IQR) | 486 | 53 (44, 61) | 49 (42, 59) | 0.20 |
| Female sex, n (%) | 486 | 355 (79.6) | 33 (82.5) | 0.70 |
| Race, n (%) | <0.001 | |||
| White | 339 (76.0) | 26 (65.0) | Ref. | |
| Black | 64 (14.3) | 1 (2.5) | 0.10 | |
| Asian | 30 (6.7) | 11 (27.5) | <0.001 | |
| Other | 13 (2.9) | 2 (5.0) | 0.30 | |
| Hispanic ethnicity, n (%) | 486 | 77 (17.3) | 8 (20.0) | 0.70 |
| SSc duration at time of HRCT (years), median (IQR) | 486 | 4 (2, 10) | 6 (3, 11) | 0.30 |
| Diffuse cutaneous subtype, n (%) | 486 | 219 (49.1) | 23 (57.5) | 0.30 |
| Modified Rodnan skin score closest to HRCT, median (IQR) | 480 | 7 (3, 15) | 4 (3, 12) | 0.20 |
| Positive ANA, n (%) | 484 | 432 (97.3) | 39 (97.5) | >0.90 |
| Positive anti-topoisomerase-I antibody, n (%) | 486 | 166 (37.2) | 14 (35.0) | 0.80 |
| Positive ACA, n (%) | 481 | 36 (8.1) | 3 (7.7) | >0.90 |
| Positive anti-RNA polymerase 3 antibody, n (%) | 429 | 84 (21.3) | 9 (25.7) | 0.50 |
| FVC %predicted on PFTs closest to HRCT, median (IQR) | 482 | 71 (60, 85) | 69 (58, 81) | 0.40 |
| DLCO %predicted on PFTs closest to HRCT, median (IQR) | 458 | 55 (42, 67) | 58 (40, 69) | >0.90 |
| Percent of lung involved on HRCT, n (%) | 486 | 0.60 | ||
| <20% | 209 (46.9) | 22 (55.0) | ||
| 20–50% | 180 (40.4) | 13 (32.5) | ||
| >50% | 57 (12.8) | 5 (12.5) |
FAM13A rs2609255 genotyping failed in three participants. IQR: interquartile range; HRCT: high-resolution CT; PFTs: pulmonary function tests; DLCO: diffusion capacity for carbon monoxide.
Differential gene expression in SSc and eQTL/pQTL analysis
While FAM13A expression was not significantly increased in the skin of patients with early dcSSc based on our previous global gene expression studies [15], FAM13A transcript levels were significantly increased in the peripheral blood cells of SSc patients. Specifically, comparison of SSc peripheral blood cell samples obtained at the baseline visit of the SCOT (Scleroderma: Cyclophosphamide or Transplantation) trial [16] (consisting of 62 untreated dcSSc patients) to 1:1 age- and sex-matched unaffected controls revealed that FAM13A levels were significantly higher in SSc (fold change = 1.3, P-value <10−7) [17]. Next, we performed a cis expression quantitative trait loci (eQTL) analysis based on publicly available databases, and found that the rs2609255 minor allele was associated with increased FAM13A transcript levels in the blood (based on the data from 31 684 individuals participating in eQTLGen Consortium cohorts) [18], CD4+ T cells (based on data from 169 population-based individuals in the UK) [19] and monocytes (based on data from 228 volunteers of European ancestry in the UK) [20]. Similarly, a cis protein quantitative trait loci (pQTL) analysis based on a recently published study in 54 219 UK Biobank participants showed that the rs2609255 minor allele was associated with increased FAM13A plasma protein levels [21].
Discussion
In this cohort of 489 SSc-ILD patients from four Scleroderma Programs in the USA, 4.7% of participants had a definite UIP pattern on HRCT. Homozygosity for FAM13A SNP rs2609255 minor allele was associated with a definite UIP pattern among SSc-ILD patients. A subgroup analysis among non-Hispanic White participants revealed similar trends. Notably, the MUC5B SNP rs35705950 was not associated with a definite UIP pattern in SSc-ILD, either in the entire cohort or among non-Hispanic White participants only.
Our study, using robust and validated image analysis, reports the lowest radiographic prevalence of UIP in a cohort of SSc-ILD patients to date. One possible explanation is that previous studies may have included both definite and probable UIP in the UIP group. In a single-centre retrospective cohort study of adults with autoimmune-ILD, the prevalence of radiographic UIP in patients with SSc-ILD was 17% (15 of 88) [3]. The prevalence of UIP in histopathologic studies was higher than the radiographic prevalence of definite UIP reported in our study. For example in a histopathologic analysis of 80 surgical lung biopsies from patients with SSc-ILD, 6 (7.5%) had UIP [1]. In another series of surgical lung biopsies from 19 patients with SSc-ILD, the prevalence of UIP was 26% [2]. In a retrospective cohort study of 22 patients with lcSSc with clinically significant ILD who underwent lung biopsy, 8 (36%) had a UIP pattern [4].
Interestingly, we did not detect an association between the MUC5B SNP rs35705950 and SSc-UIP, which is remarkable because several other forms of UIP are associated with this MUC5B SNP, including IPF, familial pulmonary fibrosis and RA-ILD [7, 8]. This suggests that SSc-UIP may potentially have a different biological underpinning, which deserves further investigation.
The FAM13A gene encodes a protein involved in small GTPase-mediated signal transduction [22]. Recent studies indicate that FAM13A is involved in both Wnt and TGF-ß2 signalling [23–25], which might be relevant for the pathogenesis of lung fibrosis. In human lung fibroblasts, expression of FAM13A can be induced by hypoxia [26]. In the healthy lung, FAM13A is expressed in airway mucosal and epithelial cells, club cells, alveolar type II epithelial cells and macrophages [25–27]. The FAM13A SNP rs2609255 has been previously identified as a risk locus for chronic obstructive pulmonary disease, as well as for IPF and other fibrotic idiopathic interstitial pneumonias [11]. The FAM13A SNP rs2609255 was associated with an increased risk of ILD in an inception cohort of RA patients from northern Sweden [28] and with UIP in RA patients from Japan [29]. Our study suggests that the FAM13A SNP rs2609255 is also a risk factor for UIP in patients with SSc. Interestingly, expression of FAM13A was shown to be the most highly upregulated gene expressed in peripheral blood mononuclear cells from patients with SSc compared with healthy controls, but whether this expression was associated with ILD in this cohort was not examined [30].
There are some limitations of our study. Our findings have not been confirmed in a separate cohort of SSc-ILD patients, however our cohort was comprised of SSc-ILD patients from four different Scleroderma Programs in the USA which increases the likelihood that we have investigated a nationally representative sample of patients. Moreover, we have not adjusted for multiple comparisons in our analyses; thus, our results are hypothesis-generating, which underscores the importance of replicating the association of FAM13A SNP rs2609255 with the UIP pattern in patients with SSc-ILD in future studies. Our eQTL analysis has also limitations. It was performed based on publicly available data and we did not measure directly the differential expression of FAM13A based on rs2609255 variant status in the participating SSc patients. Moreover, the reported eQTL analysis did not include important cell types present in the lung tissue such as pulmonary epithelial cells and fibroblasts. Lastly, the eQTL analysis suggests only relationship and does not establish causality, as the investigated SNP might be in linkage disequilibrium with the actual causal gene variant.
In conclusion, we identified a 4.7% prevalence of UIP on HRCT in patients with SSc-ILD from a large four-centre SSc-ILD cohort. We identified a novel association between the FAM13A SNP rs2609255 and SSc-UIP. Future studies are needed to establish the expression, function and pathogenic role of FAM13A in SSc-UIP as this will also advance our understanding of SSc-ILD pathogenesis.
Contributor Information
Elana J Bernstein, Division of Rheumatology, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA.
Francesco Boin, Division of Rheumatology, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Brett Elicker, Department of Radiology, University of California, San Francisco, San Francisco, CA, USA.
Yiming Luo, Division of Rheumatology, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, USA.
Yawen Ren, Division of Rheumatology, Department of Medicine, University of Colorado, Denver, CO, USA.
Meng Zhang, Division of Rheumatology, Department of Medicine, University of Texas Health Science Center at Houston (UTHealth Houston), Houston, TX, USA.
John Varga, Division of Rheumatology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.
Shervin Assassi, Division of Rheumatology, Department of Medicine, University of Texas Health Science Center at Houston (UTHealth Houston), Houston, TX, USA.
Data availability
The data underlying this article will be shared on reasonable request to the corresponding author.
Funding
This study was supported by an investigator-initiated grant from Boehringer Ingelheim. The investigators were also supported by National Institutes of Health (NIH)/National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) grant K23-AR-075112 (E.J.B.), R33AR078078 (S.A.), R01AR081280 (S.A.), NIH/National Heart, Lung, and Blood Institute grant R01-HL-164758 (E.J.B.) and Department of Defence grants W81XWH-22-1-0162 (S.A.), W81XWH-22-1-0163 (E.J.B.) and W81XWH-21-1-0768 (F.B.).
Disclosure statement: This study was funded by an investigator-initiated grant from Boehringer Ingelheim to E.J.B. In addition, E.J.B. reports consulting fees from Boehringer Ingelheim and Cabaletta and grant support from Boehringer Ingelheim and aTyr. F.B. reports consultancy fees from Adicet Bio and grant support from Leadiant Biosciences. S.A. reports consultancy fees from Boehringer Ingelheim, AstraZeneca, Abbvie, Merck, TeneoFour, aTyr, CSL Behring and Cantargia, and grant support from Boehringer Ingelheim, aTyr and Janssen. The remaining authors have declared no conflicts of interest.
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Data Availability Statement
The data underlying this article will be shared on reasonable request to the corresponding author.