Submitted:
25 June 2026
Posted:
29 June 2026
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Abstract
Background: To investigate the effects of biologic and targeted synthetic therapies on retinal microvascular parameters assessed by optical coherence tomography angiography (OCTA) in patients with axial spondyloarthritis (axSpA).
Methods: This cross-sectional study included 159 eyes of 82 patients with radiographic or non-radiographic axSpA receiving tumor necrosis factor inhibitors (TNFi), interleukin-17 inhibitors (IL-17i), or Janus kinase inhibitors (JAKi) for at least one year. All patients had low disease activity at the time of examination (BASDAI < 3). Comprehensive ophthalmic evaluation and swept-source OCTA imaging were performed. The superficial capillary plexus vessel density and foveal avascular zone (FAZ) areas in both the superficial (SCP) and deep capillary plexus (DCP) were assessed. Statistical analyses were adjusted for age, sex, smoking status, history of uveitis, treatment duration, and ocular variables.
Results: Significant differences were observed among treatment groups in the deep foveal avascular zone (DCP-FAZ) area (P = 0.0060). Post-hoc analyses revealed larger DCP-FAZ values in patients treated with TNFi compared with IL-17i (P = 0.0010), and in those treated with IL-17i compared with JAKi (P = 0.0151). No significant differences were found in superficial FAZ area or superficial capillary plexus vessel density between treatment groups. Patients receiving JAKi were older and had shorter treatment duration compared with the other groups. Smoking status was associated with a significantly smaller deep FAZ area (P = 0.0019), whereas superficial FAZ measurements remained unaffected. A weak positive correlation was observed between intraocular pressure and deep FAZ area (r = 0.18, P = 0.0237), and treatment duration was positively correlated with deep FAZ size (rho = 0.16, P = 0.0454).
Conclusions: Different classes of biologic and targeted synthetic therapies are associated with distinct retinal microvascular characteristics in patients with axSpA. The observed differences in deep FAZ measurements suggest that treatment-specific effects on retinal microcirculation may persist despite low systemic disease activity. OCTA may serve as a valuable non-invasive tool for detecting subclinical vascular alterations and monitoring ocular microvascular involvement in axSpA. Further longitudinal studies are required to clarify the clinical significance and long-term implications of these findings.
Keywords:
axial spondyloarthritis
; optical coherence tomography angiography
; retinal microcirculation
; foveal avascular zone
; TNF inhibitors
; IL-17 inhibitors
; JAK inhibitors
; biologic therapy
1. Introduction
Axial spondyloarthritis (axSpA) is a chronic inflammatory rheumatic disorder primarily affecting the axial skeleton, particularly the spine and sacroiliac joints [1]. In addition to musculoskeletal involvement, the disease is frequently associated with extra-articular manifestations, including uveitis, psoriasis, and inflammatory bowel disease (IBD) [2].
Based on imaging findings, axSpA is classified into radiographic axSpA (r-axSpA), formerly known as ankylosing spondylitis, and non-radiographic axSpA (nr-axSpA). Although these subtypes differ in the presence of structural sacroiliac joint changes visible on conventional radiography, they share similar clinical manifestations, disease burden, and treatment strategies [2,3,4]
Among extra-articular manifestations, acute anterior uveitis is one of the most common and affects approximately 6–30% of patients, particularly those who are HLA-B27 positive [5].
The diagnosis of axSpA is currently based on the Assessment of SpondyloArthritis International Society (ASAS) classification criteria [3]
Disease activity is commonly assessed using the Ankylosing Spondylitis Disease Activity Score (ASDAS) and the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI). The primary treatment goal in axSpA is remission or, alternatively, low disease activity [4]
In the pathogenesis of axSpA, the pro-inflammatory cytokines interleukin-17 and tumor necrosis factor alpha (TNF-α) play a role. [6,7] .
In patients with SpA, endothelial dysfunction occurs even in the early stages of the disease [8].
In the vasculature, IL-17 promotes the production of proinflammatory cytokines, chemokine and adhesion molecules, enhances effects of TNF and leukocyte trafficking and recruitment. As a consequence, elevated level of this cytokine may contribute to vascular inflammation and is implicated in endothelial dysfunction [9].
Tumor necrosis factor alpha (TNF-α) is a proinflammatory cytokine that may impair endothelial function and promote oxidative stress. [7]
Janus kinases (JAKs) are a family of intracellular tyrosine kinases that act as signal transducers, mediating the transmission of extracellular cytokine signals and activating downstream proteins involved in cellular signaling pathways (JAK-STAT).
The JAK–STAT proteins amplifie the effects of pro-inflammatory cytokines involved in the pathogenesis of various diseases, including axSpA [10].
By inhibiting JAK–STAT signaling, JAK inhibitors may protect the vascular endothelium through the reduction of IL-6-mediated inflammatory responses induced by TNF and IL-17A.
The introduction of biologic therapies, such as TNFi and IL-17i, as well as targeted synthetic disease-modifying drugs, such as JAKi, has significantly improved the treatment of systemic disease. TNFi alleviate both systemic and local inflammation, reduce vascular permeability, inhibit endothelial activation, and help prevent long-term tissue damage. IL-17i alleviate inflammation by regulating neutrophil recruitment, while JAKi disrupt intracellular cytokine signaling, resulting in broad immunomodulatory effects. [11,12]
Although these therapies are primarily evaluated for clinical efficacy and systemic safety, their potential impact on retinal microvascular parameters remains still not fully understood.
Optical coherence tomography angiography (OCTA) is a non-invasive imaging method that provides highly detailed, three-dimensional images of the entire microcirculation of the retina and choroid, enabling an assessment of retinal blood flow. This method allows for the identification of retinal vessels by detecting and measuring the movement of blood cells within them without the need for dye injection. [13,14]
Given the close relationship between systemic inflammation and retinal microcirculation, OCTA parameters can provide objective biomarkers of treatment-related changes in retinal structure and perfusion. Changes in the FAZ area and density of the superficial and deep capillary plexus may indicate disturbances in the vascular integrity of the retina.
The aim of our study was to compare changes in microcirculation in patients with axSpA treated with biologic therapies, such as TNFi and IL-17i, as well as targeted synthetic disease-modifying drugs, such as JAKi, using OCTA.
2. Material and Methods
This cross-sectional study was conducted between May 2025 and March 2026 at the Świat Oka Eye Center in Warsaw, Poland. The study included 159 eyes of 82 patients diagnosed with axSpA receiving biological and targeted synthetic disease-modifying drugs: TNFi, IL-17i or JAK-i. The participants were referred from biological therapy centre of the National Institute of Geriatrics, Rheumatology and Rehabilitation. The study protocol was approved by the Bioethics Committee at the National Institute of Geriatrics, Rheumatology and Rehabilitation named after Prof. Eleonora Reicher on 20 March 2025 under approval No. KBT-3/1/2025, and was carried out in accordance with the tenets of the Declaration of Helsinki.
The inclusion criteria were: diagnosis of axial spondyloarthropathy – radiological or non-radiological form, biological treatment for at least 1 year – anti-TNF-alpha drugs, IL-17 inhibitor, JAK, age: 20-50 years. Exclusion criteria were: myopia (≥ 3.0 Dpsh), hyperopia (≤ 3.0 Dpsh), active uveitis, glaucoma, ocular hypertension, history of intraocular or intracranial surgery, history of optic neuritis, history of optic disc oedema, diabetic retinopathy, uncontrolled arterial hypertension, hereditary retinal degeneration, lack of written consent to participate in the study. Eyes with poor-quality OCT-A images, segmentation errors, or significant motion artifacts were also excluded from the analysis.
All patients met the classification criteria for the Assessment of SpondyloArthritis international Society (ASAS) criteria. AxSpA patients were divided into three groups (TNF alpha-i, il 17- i, JAK-i) in further analyses. At the time of the study, all patients had low disease activity (BASDAI<3).
Study participants underwent a complete ophthalmic examination, including slit lamp biomicroscopy with dilated fundus examination using a 90-diopter (D) lens, best-corrected visual acuity (BCVA) which was measured using a Snellen chart, refractive error, and intraocular pressure measurement (non-contact tonometry using autokeratorefractotonometr TOPCON TRK-2P).
Multimodal imaging was performed using a Swept-Source OCT (SS-OCT) device (Topcon DRI OCT Triton, Tokyo, Japan). The OCTA was performed using 4.5 × 4.5 mm images centered on the macula. On OCTA images, capillary plexus density (CPD) of the vessels in the parafoveal and perifoveal regions was evaluated in the superficial capillary plexus (SCP). The scan automatically inserted fovea-centered circles at the macula, detecting SCP. The SCP network was segmented from 3 μm beneath the internal limiting membrane to 15 μm below the inner plexiform layer (IPL). The foveal vessel density was defined as the area of the small circle, with a diameter of 1 mm. The parafoveal vessel density was defined as the area of the outer circle. It was automatically divided into four quadrants: superior (S), inferior (I), nasal (N), and temporal (T). The vessel density was automatically calculated as a percentage, according to the area occupied by blood vessels, by the software. The average vessel density of the SCP in the four quadrants was calculated. The software used does not measure vascular density in the DCP. The foveal avascular zone (FAZ) was measured manually by the same researcher, in both the superficial capillary plexus (SCP) and the deep capillary plexus (DCP) by the same researcher. Two scans for each eye were captured, and the best one in terms of quality was considered for the analysis.
All participants were examined at a similar time of day, between 11:00 AM and 1:00 PM.
Information on smoking status and history of uveitis was collected for all participants. All patients met the classification criteria for the Assessment of SpondyloArthritis international Society (ASAS) criteria [12].AxSpA patients were divided into two subgroups (r-and nr- axSpA) in further analyses. Forty three of 70 patients with axSpA were treated with anti TNF-a. None of our patients had active anterior uveitis during the measurements. Informed consent was obtained from all subjects involved in the study.
Statistical Procedures
Categorical variables were shown as integer numbers and percentages (frequencies). Numerical traits were described through their mean, median, standard deviation, standard error 95% confidence interval, and lower-to-upper quartile values. The normality of distribution was assessed by using the Shapiro–Wilk W test. Levene’s test was used to test the homogeneity of variances. A multifactor analysis of variance (ANOVA) without replications was carried out in order to test the differences of normally distributed variables. Generalized linear models (GZM) were fitted when dealing with non-normally distributed variables or heterogenic variances. All the multifactor procedures were controlled for the study participants’ age, gender, smoking status, history oof uveitis, biological treatment duration and selected OCT measures. The Pearson product-moment correlation coefficients were obtained when assessing relationships between numerical traits. Sperman’s rank correlation was fitted for the treatment duration due to its strong non-normal distribution. Considering the participants’ binocular vision, an appropriate error correction method (intra-subject correlations) was introduced into the calculations. A level of p < 0,05 was deemed statistically significant. All the procedures were carried out using Statistica™, release 13.3 (TIBCO Software Inc., Palo Alto, CA, U.S.A.), and StatsDirect Statistical Software, version 4 (StatsDirect Ltd, Liverpool, England).
3. Results
The study included 159 eyes of 82 patients diagnosed with axSpA, taking biological agents with mean treatment duration 44.33 months. Among the analysed patients, 31 individuals (60 eyes, 38.99%) were treated with TNFi. The most frequently used agent was Adalimumab, administered to 15 patients (30 eyes, 18.87%), followed by Golimumab in 9 patients (18 eyes, 11.32%), Etanercept in 4 patients (8 eyes, 5.03%), and Certolizumab pegol in 3 patients (6 eyes, 3.77%). IL-17i were used in 30 patients (39.48%). Within this group, Secukinumab was administered to 26 patients (50 eyes, 31.45%), whereas Ixekizumab was used in 4 patients (8 eyes, 5.03%). JAKi were administered to 20 patients (39 eyes, 24.53%). Upadacitinib was used in 19 patients (37 eyes, 23.27%), while Tofacitinib was administered to 1 patient (2 eyes, 1.26%). (Table 1.)
The demographic and basic clinical characteristics of the groups are presented in Table 1.
The structure of the three therapeutic groups by gender was statistically significantly diverse (P=0.0269). In the study group with IL=17 inhibitors, men clearly outnumbered women. Male patients also prevailed in the group with JAK inhibitors. The discussed disproportions were less pronounced in the group with anti-TNF-α. (Tab. 2.)
Study participants administering anti-TNF-α reported uveitis statistically significantly more frequently than other subjects (P=0.0046). (Tab. 2.)
The study participants who were administering JAK inhibitors were statistically older than the remaining two groups (P=0.0389). The age of participants taking anti-TNF-α and IL-17 inhibitors was equalized. (Tab. 2.)
There were observed statistically significant differences in the deep foveal avascular zone between the study groups (P=0.0060). Post-hoc tests showed significant differences between the group with anti-TNF-α versus IL-17 inhibitors (P=0.0010) and IL-17 inhibitors versus JAK inhibitors (P=0.0151). (Tab. 2.)
The treatment duration was statistically significantly shortest in the group with JAK inhibitors (P=0.0007). (Tab. 2.)
Table 2.
Baseline characteristics of the study participants’ eyes by therapeutic group (n = 82 individuals = 159 eyes).
Table 2.
Baseline characteristics of the study participants’ eyes by therapeutic group (n = 82 individuals = 159 eyes).
| Analyzed trait | Anti-TNF-α | IL-17 inhibitors | JAK inhibitors | P value |
|---|---|---|---|---|
| n (%) | ||||
| No. of eyes | 62 (38.99) | 58 (39.48) | 39 (24.53) | n/a |
| Gender: | ||||
|
18 (56.25) | 7 (23.33) | 7 (35.00) | 0.0269 |
|
14 (43.75) | 23 (76.67) | 13 (65.00) | |
| History of uveitis | 17 (27.42) | 4 (6.90%) | 5 (12.82) | 0.0046 |
| Smoking | 10 (31.25) | 7 (23.33) | 7 (35.00) | 0.6419 |
| M (SD), Me (Q1-Q3) | ||||
| Age [y] | 34.63 (6.93) | 34.91 (7.40) | 38.64 (7.54) | 0.0164 |
| T [mmHg] | 16.43 (2.66) | 17.01 (2.26) | 16.69 (2.41) | 0.8315 |
| BCVA [logMAR] | 1.00 (0.00) | 0.99 (0.04) | 1.00 (0.00) | 0.2442 |
| Superficial FAZ [mm2] | 260.68 (96.75) | 259.11 (122.74) | 242.75 (124.91) | 0.8497 |
| Deep FAZ [mm2] | 600.84 (225.90) | 566.52 (180.21) | 465.23 (213.23) | 0.0060 |
| AL [mm] | 23.70 (1.06) | 23.65 (0.99) | 23.83 (0.79) | 0.8315 |
| Treatment duration [m] | 39 (24-58) | 38 (24-65) | 27 (19-30) | 0.0007 |
Table 3.
Descriptive statistics for the density of the superficial plexus vessels [%] in the study participants’ eyes by therapeutic group (n = 159 eyes).
Table 3.
Descriptive statistics for the density of the superficial plexus vessels [%] in the study participants’ eyes by therapeutic group (n = 159 eyes).
| Density [%] |
Anti-TNF-α | IL-17 inhibitors | JAK inhibitors | P value |
|---|---|---|---|---|
| M (SD) | ||||
| Central | 18.25 (4.16) | 19.34 (4.48) | 18.54 (5.26) | 0.2846 |
| Superior quadrant | 48.56 (1.95) | 47.71 (2.87) | 48.14 (2.58) | 0.1025 |
| Inferior quadrant | 48.42 (2.61) | 47.89 (3.71) | 47.99 (2.09) | 0.4370 |
| Nasal quadrant | 46.84 (2.17) | 45.97 (2.51) | 46.64 (2.31) | 0.1070 |
| Temporal quadrant | 47.74 (2.03) | 47.22 (2.33) | 47.93 (2.19) | 0.1381 |
(M – mean, SD – standard deviation; MT – macular thickness.).
Significant differences were observed between smokers and non-smokers within the study population. The superficial foveal avascular zone did not differ statistically significantly in the study participants by smoking status (P=0.2303). However, the deep FAZ revealed a large difference between the smokers and the non-smokers (P=0.0019). (Tab. 4)
The biological treatment duration was statistically significantly longer in the study participants who smoked as compared to the non-smokers (P=0.0386). (Tab. 4)
Table 4.
Descriptive statistics for selected measurements in the study participants’ eyes by smoking status (n = 159 eyes).
Table 4.
Descriptive statistics for selected measurements in the study participants’ eyes by smoking status (n = 159 eyes).
| Analyzed variable | Smokers | Non-smokers | P value |
|---|---|---|---|
| M (SD), Me (Q1-Q3) | |||
| Superficial FAZ [mm2] | 243.02 (113.09) | 261.03 (113.60) | 0.2303 |
| Deep FAZ [mm2] | 493.65 (189.43) | 580.83 (217.31) | 0.0019 |
| Treatment duration [m] | 24 (19-54) | 36 (25-52) | 0.0386 |
(M – mean, SD – standard deviation; CT – choroidal thickness, RT – retinal thickness, GCC – ganglion cell complex, FAZ - foveal avascular zone, MT – macular thickness. RNFL – retinal nerve fiber layer.).
A weak positive correlation was observed between intraocular pressure and deep FAZ area (r = 0.18, P = 0.0237). Treatment duration demonstrated a weak positive monotonic correlation with deep FAZ (rho = 0.16, P = 0.0454).
Selected, statistically significant, Pearson correlation r coefficients for the examined eyes:
- ▪
- Ocular tension and deep FAZ, r = 0.18 (P=0.0237)
Selected, statistically significant, Spearman’s rank correlation rho coefficients for the examined eyes:
- ▪
- Treatment duration and deep FAZ, rho = 0.16 (P=0.0454)
4. Discussion
In this study, we observed significant differences between the treatment groups in retinal microvascular parameters, including the FAZ area in the DCP. These findings suggest that biologic therapies and targeted synthetic disease-modifying drugs may have different effects on ocular microcirculation. To the best of our knowledge, this is the first study to directly compare the effects of different classes of these therapies on selected parameters of retinal microcirculation.
Nowadays, many authors emphasize the importance of assessing retinal microcirculation in clinical practice among patients with rheumatic diseases.
Previous studies have revealed that patients with rheumatic diseases may have subclinical microvascular retinal abnormalities, even in the absence of apparent concomitant cardiovascular disease. The increased diameter of retinal venules observed in these patients suggests early vascular dysfunction associated with chronic systemic inflammation. [15]
Some researches on inflammatory rheumatic diseases also have shown that an increased diameter of retinal venules is associated with greater disease activity, suggesting the presence of systemic microvascular involvement linked to chronic inflammation. Interestingly, these changes were observed regardless of CRP levels, indicating that changes in retinal microvessels may reflect the severity of inflammation more sensitively than conventional laboratory markers. [16]
Previous trials in rheumatoid arthritis which, similarly to axSpA, is a chronic inflammatory joint disease, have shown that effective immunomodulatory therapy can improve microvascular abnormalities in the retina in line with a reduction in systemic disease activity. In particular, treatment with a particular biological DMARD was associated with a significant reduction in the wall-to-lumen ratio of retinal arterioles after 12 months, suggesting partial reversibility of inflammation-related microvascular remodeling. [17]
A 2020 publication showed that patients with ankylosing spondylitis exhibit subtle microvascular abnormalities in the retina, including altered vascular tortuosity and increased retinal vascular density, which may reflect early vascular dysfunction associated with an increased risk of cardiovascular disease. Interestingly, some of these changes appeared to be more pronounced in male patients, suggesting that sex may influence microvascular changes. [18]
These results support the concept that assessment of retinal vessels may provide valuable insight into subclinical vascular dysfunction in systemic inflammatory diseases and serve as a sensitive biomarker of microvascular involvement during the course of these conditions. They also confirm the view that effective systemic control of inflammation may have a beneficial effect on retinal microcirculation, potentially explaining the microvascular changes observed in our cohort.
Previous studies using OCT angiography have revealed a reduced capillary density in the macular region in patients with axSpA, which suggests the presence of subclinical microvascular abnormalities. Importantly, these changes were associated with longer disease duration rather than current disease activity, indicating a cumulative effect on retinal microcirculation. [19]. However, our results did not reveal any significant differences in superficial vascular density between the treatment groups, but only differences in the FAZ area in the DCP, which may reflect the effect of systemic therapy on retinal microcirculation. These discrepancies suggest that although axSpA may be associated with changes in microcirculation, effective treatment may alleviate or mask these changes, particularly in cross-sectional analyses.
Some researches have shown that patients with axSpA exhibit subclinical microvascular changes, including enlargement of the avascular zone of the macula and reduced vascular density in both the superficial and deep vascular plexuses, despite ongoing treatment. Importantly, although anti-TNF therapy effectively suppresses systemic inflammation, it does not completely prevent these microvascular changes, suggesting a persistent effect of chronic inflammation on retinal circulation. [20]. Comparatively, our results revealed differences in the the FAZ of DCP between treatment groups, which may reflect the varying effects of therapeutic agents on retinal microcirculation. These observations support the hypothesis that even during biological therapy, subtle changes in blood vessel structure may persist, which vary depending on the mechanism of action of a drug in question.
One of the ophthalmic manifestations of axSpA may be non-infectious choroiditis. Other researchers have shown that this condition, and particularly posterior choroiditis, is associated with a significant enlargement of the deep avascular zone of the macula, regardless of the presence of macular edema. In contrast, anterior uveitis seems to affect the parameters of this zone mainly in cases accompanied by macular edema, whereas eyes without edema do not differ significantly from those of healthy individuals in the control group. These findings suggest that the DCP is particularly susceptible to inflammatory damage [21].
Given our findings, the observed differences in the deep FAZ between the treatment groups may reflect varying degrees of microvascular involvement or residual effects of inflammation. This may indicate changes in the deep microcirculation of the retina may remain even in the absence of overt clinical inflammation and may be modulated by the type of systemic therapy.
Our study also revealed significant differences depending on smoking status. Interestingly, whilst smoking had no significant effect on the FAZ of the SCP, a marked difference was observed between smokers and non-smokers in the case of the deep FAZ. This finding may indicate that the deeper microcirculation of the retina is more susceptible to changes caused by smoking.
Previous large population-based studies have shown that cigarette smoking is an independent factor associated with reduced vascular density in the deep capillary plexus, with a dose-dependent relationship observed. These results suggest that smoking has a detrimental effect on retinal microcirculation, particularly in the deeper vascular layers, which may contribute to the development of eye diseases [22].
In the context of our findings, these observations suggest that smoking may affect microcirculation in the retina, although these effects may vary depending on the study population and accompanying systemic treatments.
Prior observations have shown that long-term smoking can affect the microcirculation of the retina and choroid in various ways, with some evidence of increased density of the deep retinal vessels, despite the absence of significant changes in the density of the superficial plexus or the overall thickness of the choroid. Importantly, a negative correlation has also been reported between cumulative smoking exposure and choroidal thickness, suggesting long-term harmful effects on the vascular system [23]
These findings suggest a complex and potentially dual effect of smoking on ocular circulation, likely mediated by mechanisms such as endothelial dysfunction and impaired vascular regulation, and may partly explain the differences observed across studies.
Some authors have demonstrated that long-term smoking is associated with an enlargement of the FAZ and changes in retinal vascular density, suggesting a significant impairment of microcirculation. [24]
This confirms the hypothesis that chronic smoking can induce both structural and vascular changes in the retina, potentially through mechanisms related to endothelial dysfunction, hypoxia, and chronic oxidative stress, even in the absence of differences in overall retinal thickness, highlighting its potential impact on eye health at a subclinical level.
Limitations: This study has several limitations that should be taken into account. First, the group receiving JAKi included fewer patients than the groups receiving TNFi and IL-17i, which may have affected the statistical power and generalizability of the results. Second, there were significant differences in baseline characteristics between the groups, including age and gender distribution. Patients receiving JAKi were significantly older, and the preponderance of men was more pronounced in the groups receiving IL-17i and JAKi, which may have introduced potential interference factors. In addition, the duration of treatment was significantly shorter in the group of patients receiving JAKi, which may have influenced the observed results and limited the possibility of a direct comparison between the different therapies. Moreover, the absence of vessel density measurements in the DCP, which would be a valuable addition to the collected data. Furthemore, FAZ area was measured manually, which may introduce interobserver variability despite standardized measurement protocols. Finally, the cross-sectional nature of the study precludes drawing conclusions regarding a cause-and-effect relationship and does not allow for the assessment of changes in ophthalmic parameters over time.
In summary, significant differences were observed in retinal microcirculation parameters assessed by OCTA in patients with axSpA treated with various therapeutic agents. The results suggest that biologic therapies and targeted synthetic disease-modifying drugs may have different effects on retinal vascular perfusion and microvascular architecture. Retinal imaging may provide a sensitive, noninvasive tool for detecting subclinical vascular changes in rheumatic inflammatory diseases, including axSpA, and the condition of the retinal vessels may serve as a “window” into systemic microangiopathy in spondyloarthropathies. OCTA appears to be a promising, non-invasive tool for monitoring treatment-related vascular changes in the eye in patients with axSpA. Further studies involving larger, long-term cohorts and utilizing automated measurement techniques are needed to confirm these preliminary findings and biologic therapies and targeted synthetic disease-modifying drugs.
Supplementary Materials
no Supplementary Materials are provided.
Author Contributions
Conceptualization, I.J., J.G., A.F.-G.; methodology I.J., J.G..; software J.G. ,I.J.; validation, J.G., A.F.-G.; formal analysis I.J., J.G.; investigation I.J., M.Ł.; resources M.Ł., A.F.-G. ; data curation, I.J., M.Ł.; writing—I.J., M.Ł.; writing—J.G.; visualization, I.J., J.G.; supervi-sion, J.G., A.F.-G.; project administration I.J., A.F.-G.
Funding
This research received no external funding.
Institutional Review Board Statement
The study was conducted in accordance with the Decla-ration of Helsinki, and approved by the Ethics Committee of National Institute of Geriatrics, Rheumatology and Rehabilitation (20 March 2025 under approval No. KBT-3/1/2025).
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
The data presented in this study are available on request from the corresponding author due to patient privacy and confidentiality restrictions.
Acknowledgments
Artificial intelligence tools were employed to support language editing, grammatical correction, and translation. The authors assume full responsibility for the scientific content and interpretations presented in this manuscript.
Conflicts of Interest
The authors declare no conflict of interest.
References
- Katsifis-Nezis, D.; Fanouriakis, A., Mediterranean journal of rheumatology 2026, 37 (Suppl 1), 1–11. [CrossRef]
- Ramiro, S.; Nikiphorou, E.; Sepriano, A.; Ortolan, A.; Webers, C.; Baraliakos, X.; Landewé, R.B.M.; den Bosch, V.; Filip E; Boteva, B.; Bremander, A.; Carron, P.; Ciurea, A.; van Gaalen, F.A.; Géher, P.; Gensler, L.; Hermann, J.; de Hooge, M.; Husakova, M.; Kiltz, U.; López-Medina, C.; Machado, P.M.; Marzo-Ortega, H.; Molto, A.; Navarro-Compán, V.; Nissen, M.J.; Pimentel-Santos, F.M.; Poddubnyy, D.; Proft, F.; Rudwaleit, M.; Telkman, M.; Zhao, S.S.; Ziade, N.; van der Heijde, D., Annals of the rheumatic diseases 2023, 82 (1), 19–34. [CrossRef]
- Ghosh, N.; Ruderman, E.M.; Arthritis research & therapy 2017, 19 (1), 286. [CrossRef]
- Poddubnyy, D.; Navarro-Compán, V.; Torgutalp, M.; Arends, S.; Aydin, S.Z.; Battista, S.; van den Bosch, F.; Bundy, C.; Cauli, A.; Davies, J.; Dougados, M.; Duruöz, T.; El-Zorkany, B.; Fong, W.; van Gaalen, F.; Garcia-Salinas, R.; Cumbrera, M.G.; Géher, P.; Gensler, L.; Grazio, S.; Huang, F.; Kishimoto, M.; Landewé, R.; Leung, Y.Y.; Machado, P.M.; Marzo-Ortega, H.; Meghnathi, B.; Molto, A.; Nikiphorou, E.; Ramiro, S.; Rudwaleit, M.; Saad, C.G.S.; Sepriano, A.; Wei, J.; Baraliakos, X.; van der Heijde, D., Annals of the rheumatic diseases 2025, 84 (4), 538–546. [CrossRef]
- Walsh, J.A.; Magrey, M., Journal of clinical rheumatology : Practical reports on rheumatic & musculoskeletal diseases 2021, 27 (8), e547-e560. [CrossRef]
- Beringer, A.; Miossec, P.; Rheumatology, N.R. 2019, 15 (8), 491–501. [CrossRef]
- Ursini, F.; Leporini, C.; Bene, F.; S. D'Angelo; Mauro, D.; Russo, E.; de Sarro, G.; Olivieri, I.; Pitzalis, C.; Lewis, M.; Grembiale, R.D.; Scientific reports 2017, 7 (1), 5346. [CrossRef]
- Łosińska, K.; Korkosz, M.; Kwaśny-Krochin, B.; Reumatologia 2019, 57 (2), 100–105. [CrossRef]
- Karbach, S.; Croxford, A.L.; Oelze, M.; Schüler, R.; Minwegen, D.; Wegner, J.; Koukes, L.; Yogev, N.; Nikolaev, A.; Reißig, S.; Ullmann, A.; Knorr, M.; Waldner, M.; Neurath, M.F.; Li, H.; Wu, Z.; Brochhausen, C.; Scheller, J.; Rose-John, S.; Piotrowski, C.; Bechmann, I.; Radsak, M.; Wild, P.; Daiber, A.; von Stebut, E.; Wenzel, P.; Waisman, A.; Münzel, T.; Arteriosclerosis; Thrombosis, and Vascular Biology 2014, 34 (12), 2658–2668. [CrossRef]
- Raychaudhuri, S.P.; Shah, R.J.; Banerjee, S.; Raychaudhuri, S.K., Current rheumatology reports 2024, 26 (6), 204–213. [CrossRef]
- Webers, C.; Ortolan, A.; Sepriano, A.; Falzon, L.; Baraliakos, X.; Landewé, R.B.M.; Ramiro, S.; van der Heijde, D.; Nikiphorou, E., Annals of the rheumatic diseases 2023, 82 (1), 130–141. [CrossRef]
- Klavdianou, K.; Papagoras, C.; Baraliakos, X., Mediterranean journal of rheumatology 2023, 34 (2), 129–138. [CrossRef]
- Jia, Y.; Tan, O.; Tokayer, J.; Potsaid, B.; Wang, Y.; Liu, J.J.; Kraus, M.F.; Subhash, H.; Fujimoto, J.G.; Hornegger, J.; Huang, D.; Optics express 2012, 20 (4), 4710–4725. [CrossRef]
- Paczwa, K.; Golebiewska, J., The Polish Journal of Aviation Medicine, Bioengineering and Psychology 2023, 26, 45–54. [CrossRef]
- Deiseroth, A.; Marcin, T.; Berger, C.; Infanger, D.; Schäfer, J.; Bannert, B.; Schmidt-Trucksäss, A.; Voll, R.E.; Kyburz, D.; Hanssen, H., Frontiers in physiology 2018, 9, 176. [CrossRef]
- Babaoğlu, H.; Baytaroğlu, A.; Torğutalp, M.; Erden, A.; Kadayıfçılar, S.; Kalyoncu, U., Turkish journal of medical sciences 2019, 49 (1), 20–26. [CrossRef]
- Piantoni, S.; Regola, F.; Angeli, F.; Caproli, A.; Trovati, A.; Tomasi, C.; Chiarini, G.; Rossini, C.; Rosei, C.A.; de Ciuceis, C.; Franceschini, F.; Muiesan, M.L.; Rizzoni, D.; Airò, P., Frontiers in medicine 2024, 11, 1247024. [CrossRef]
- van Bentum, R.E.; Baniaamam, M.; Kinaci-Tas, B.; van de Kreeke, J.A.; Kocyigit, M.; Tomassen, J.; den Braber, A.; Visser, P.J.; Wee, M.M.T.; Serné, E.H.; Verbraak, F.D.; Nurmohamed, M.T.; van der Horst-Bruinsma, I.E., Seminars in Arthritis and Rheumatism 2020, 50 (6), 1535–1541. [CrossRef]
- Koca, N.; Ayar, K.; Can, M.E.; Rheumatology international 2020, 40 (6), 901–913. [CrossRef]
- Karataş, Ö.; Pota, Ç.E.; Akyüz, B.; Atlıhan, Y.S.; Pota, K.; Yaprak, A.Ç.; Sarı, M.; Tuna, S.; Diagnostics 2025, 15 (5), 597. [CrossRef]
- Waizel, M.; Todorova, M.G.; Terrada, C.; LeHoang, P.; Massamba, N.; Bodaghi, B., Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie 2018, 256 (10), 1977–1984. [CrossRef]
- Zhu, X.; Yang, K.; Xiao, Y.; Ye, C.; Zheng, J.; Su, B.; Zheng, Y.; Zhang, X.; Shi, K.; Li, C.; Lu, F.; Qu, J.; Li, M.; Cui, L.; Acta ophthalmologica 2022, 100 (7), e1479-e1488. [CrossRef]
- Gokmen, O.; Ozgur, G., European journal of ophthalmology 2023, 33 (1), 455–462. [CrossRef]
- Aboud, S.A.-A.; Hammouda, L.M.; Saif, M.Y.S.; Ahmed, S.S., European journal of ophthalmology 2022, 32 (1), 436–442. [CrossRef]
Table 1.
Baseline characteristics of the study participants (n = 82 individuals = 159 eyes).
| Analyzed trait | n (%) | ||
|---|---|---|---|
| No. of participants | 82 (n/a) | ||
| No. of eyes | 159 (n/a) | ||
| Gender: | |||
|
32 (39.02) | ||
|
50 (60.98) | ||
| Side: | |||
|
79 (49.69) | ||
|
80 (50.31) | ||
| Biological agent: | |||
|
62 (38.99) | Adalimumab, 30 (18.87); Certolizumab, 6 (3.77); Etanercept, 8 (5.03); Golimumab, 18 (11.32) | |
|
58 (39.48) | Ixekizumab, 8 (5.03); Sekukinumab, 50 (31.45) | |
|
39 (24.53) | Tofacitinib, 2 (1.26); Upadacitinib, 37 (23.27) | |
| History of uveitis | 26 (16.35) | ||
| Smoking status | 24 (29.27) | ||
| M (SD), Me (Q1-Q3), SE (95% CI) | |||
| Age [y] | 35.72 (7.40) | 37 (30-42) | 0.58 (34.56-36.88) |
| T [mmHg] | 16.71 (2.46) | 17 (15-19) | 0.19 (16.33-17.10) |
| BCVA [logMAR] | 1.00 (0.03) | 1 (1-1) | 0.002 (0.99-1.00) |
| Superficial FAZ [mm2] | 255.71 (113.39) | 256.09 (188.26-319.57) | 8.99 (237.95-273.47) |
| Deep FAZ [mm2] | 555.06 (212.64) | 528.79 (417.66-672.56) | 16.86 (521.75-588.37) |
| AL [mm] | 23.71 (0.97) | 23.68 (23.18-24.32) | 0.08 (23.56-23.87) |
| Treatment duration [m] | 44.33 (32.05) | 34 (23-52) | 2.61 (39.17-49.48) |
(n – number, % – percentage, M – mean, SD – standard deviation, Me – median, Q – quartiles, SE – standard error, CI – confidence interval; TNF – tumor necrosis factor, IL – interleukin, JAK – Janus kinase, T – ocular tension, BCVA – best corrected visual acuity, logMAR – logarithm of the minimum angle of resolution, CT – choroidal thickness, RT – retinal thickness, GCC – ganglion cell complex, FAZ - foveal avascular zone, AL – axial length.).
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