Lei Zhu,He Li,Rong Wang,Zhaohuai Li,Sichen Zhao,Xuening Peng,Wenru Su
Identification of Hif1α as a Potential Participant in Autoimmune Uveitis Pathogenesis Using Single-Cell Transcriptome Analysis Hif1α Is Involved in Autoimmune Uveitis
single-cell RNA sequencing,uveitis,hypoxia-inducible factor-1α
Purpose This study purposed to depict the transcriptional changes associated with autoimmune uveitis (AU) pathogenesis and identify potential therapeutic targets of this disease. Methods An experimental AU (EAU) model was established with retina antigen and adjuvants. An EAU control group was established with adjuvant only to eliminate nonspecific effects. We conducted single-cell RNA sequencing (scRNA-seq) on cervical draining lymph node cells of EAU, EAU control, and normal mice to identify the EAU-associated transcriptional changes and the potential pathogenic molecules. Subsequent flow cytometry, adoptive transfer experiment, scRNA-seq analysis of human uveitis, and proliferation assessment were conducted to verify the function of the interested molecule in uveitis. Results The scRNA-seq data suggested that hypoxia-inducible factor 1 alpha (Hif1α) may participate in EAU pathogenesis via regulating T helper (Th)-17, Th1, and regulatory T cells. Hif1α inhibition alleviated EAU symptoms and regulated Th17, Th1, and regulatory T cell proportions. CD4+ T cells with repressed Hif1α expression failed to transfer EAU to naïve mice. In Vogt–Koyanagi–Harada disease, which is a human uveitis, Hif1α was also increased in CD4+ T cells and regulated their proliferation. Conclusions The results indicate that Hif1α may participate in AU pathogenesis and are, thus, a potential therapeutic target.
Identification of Hif1α as a Potential Participant in Autoimmune Uveitis Pathogenesis Using Single-Cell Transcriptome Analysis Hif1α Is Involved in Autoimmune Uveitis

This study purposed to depict the transcriptional changes associated with autoimmune uveitis (AU) pathogenesis and identify potential therapeutic targets of this disease.

An experimental AU (EAU) model was established with retina antigen and adjuvants. An EAU control group was established with adjuvant only to eliminate nonspecific effects. We conducted single-cell RNA sequencing (scRNA-seq) on cervical draining lymph node cells of EAU, EAU control, and normal mice to identify the EAU-associated transcriptional changes and the potential pathogenic molecules. Subsequent flow cytometry, adoptive transfer experiment, scRNA-seq analysis of human uveitis, and proliferation assessment were conducted to verify the function of the interested molecule in uveitis.

The scRNA-seq data suggested that hypoxia-inducible factor 1 alpha (Hif1α) may participate in EAU pathogenesis via regulating T helper (Th)-17, Th1, and regulatory T cells. Hif1α inhibition alleviated EAU symptoms and regulated Th17, Th1, and regulatory T cell proportions. CD4+ T cells with repressed Hif1α expression failed to transfer EAU to naïve mice. In Vogt–Koyanagi–Harada disease, which is a human uveitis, Hif1α was also increased in CD4+ T cells and regulated their proliferation.

The results indicate that Hif1α may participate in AU pathogenesis and are, thus, a potential therapeutic target.

Autoimmune uveitis (AU) refers to a collection of autoimmune diseases that target ocular structures, including the iris, ciliary body, choroid, retina, and vitreous. These diseases can lead to severe vision loss and are the major causes of blindness. Owing to the ease of recurrence and chronic course, AU have significant health and finical impacts on patients. The main treatments involve corticosteroids combined with immunosuppressants,; however, their long-term use may cause severe local and systemic side effects. A deeper understanding of AU pathogenesis is required for the exploration of more targeted drugs. Experimental AU (EAU) is a classic AU mice model that is induced by interphotoreceptor retinoid-binding protein 1–20 (IRBP1–20), pertussis toxin (PTX), and complete Freund's adjuvant (CFA). IRBP1–20 is the retinal autoantigen, whereas PTX and CFA are adjuvants that are critical for EAU induction. Studies based on the EAU model have provided valuable insights into AU pathogenesis, with CD4+ T cells being the focus., Effector CD4+ T (Teff) cells, usually T helper (Th)-17 and Th1 cells, dominate in AU pathogensis., Adoptive transfer of these cells induces EAU in naïve mice. Inversely, regulatory T (Treg) cells maintain immune tolerance and control inflammatory damage in AU., Teff and Treg cell imbalance occurs with AU and other autoimmune diseases.– Exploration of the abnormal Teff and Treg cell regulators in AU may help to identify potential treatment targets. Single-cell RNA sequencing (scRNA-seq) is an effective technology for analyzing single-cell transcriptiomes., Using scRNA-seq, studies have identified various pathogenic molecules and cell clusters in different diseases.– Lymph nodes (LN) are sites for immune cell interactions and antigen presentation and, thus, are important for immune response initiation., The major ocular draining LNs are cervical draining LNs (CDLN),, which may serve as important sources of autoreactive lymphocytes during autoimmune diseases involving the eyes. During EAU development, although PTX and CFA are used to overcome immunological resistance, they can also have multifaceted effects on immune responses and complex interpretation of experimental data.,– Therefore, in this study, the EAU control group was established with adjuvants only to eliminate nonspecific effects. scRNA-seq was conducted on CDLN cells of EAU, EAU control, and normal mice to delineate the EAU-associated transcriptional changes and identify potential therapeutic targets of AU.

We fed 6- to 8-week-old female mice (C57BL/6J) from the Medical Lab Animal Center (Guangzhou, China) under specific pathogen-free conditions. Animal experiments adhered to the ARVO statement and institutional policies for animal use (Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, China).

Patients with Vogt–Koyanagi–Harada (VKH) disease and healthy controls were recruited from Zhongshan Ophthalmic Center. All patients were diagnosed according to clinical manifestations and ocular examination results. No remarkable sex and age differences were between patients with VKH and healthy individuals. Informed consent was gained from all patients. All the patients were newly diagnosed and did not receive any treatment. Patients with comorbid diabetes, cancer, hypertension, and other systemic diseases were excluded. Blood samples from five patients and five healthy controls were collected for scRNA-seq. Blood samples from another 10 patients and 10 healthy controls were used to evaluate hypoxia-inducible factor 1 alpha (Hif1α) expression by flow cytometry. All experiments were allowed by the Ethics Committee of the Zhongshan Ophthalmic Center (ID: 2020KYPJ124).

EAU model was induced by 2 g/mL IRBP1–20 (GiL Biochem, Shanghai, China) emulsified in the same volume of CFA consisting of 2.5 mg mycobacterium tuberculosis (BD Difco, San Jose, CA, USA)., On days 0 and 2 after immunization, mice were injected with 0.25 µg PTX (List Biological Laboratories, Campbell, CA, USA)., Clinical scores were evaluated during fundus examination in a blinded manner.

The eyes extracted from mice were fixed in paraformaldehyde for 48 hours. Then the fixed eyes were paraffin-embedded for hematoxylin and eosin staining. Pathological scores were assessed by a blinded method.

Mice were daily injected intraperitoneally with vehicle or an Hif1α inhibitor, KC7F2 (10 mg/kg/d; Selleck Chemicals, Houston, TX, USA), for 2 weeks after immunization. CDLN cells were isolated from the EAU group and these cells were treated with IRBP1–20 alone or IRBP1–20 + KC7F2 (10 µM),, at 37°C for 72 hours before flow cytometry.

Harvested cells were stained with live/dead dye, then labeled by surface markers: anti-mouse CD4 (100434) and anti-human CD4 (344613). For intracellular staining, after fixation and permeabilization, cells were labeled by intracellular markers: anti-mouse IL-17A (506930), IFN-γ (505808), Foxp3 (11-5773-82); and anti-human Hif1α (2286400). After staining, flow cytometry was used for the detection of these cells and the data analysis was performed with FlowJo software (v10.0.7). All antibodies were purchased from BioLegend (San Diego, CA, USA).

CDLN cells obtained from the EAU group were cultured with IRBP1–20 (20 µg/mL) or IRBP1–20 (20 µg/mL) + KC7F2 (10 µM) for 72 hours and then sorted CD4+ T cells were injected into naïve mice (2 × 107 cells per mouse).

Human CD4+ T cells were obtained using flow sorter and stained with 2.5 mM carboxyfluorescein diacetate succinimidyl ester (CFSE, BD Biosciences, Franklin Lakes, NJ, USA). Then, these cells were treated with CD3/28 Dynabeads (GIBCO, Grand Island, NY, USA) or CD3/28 Dynabeads+ KC7F2 (10uM) for 3 days and subjected to flow cytometry.

We used a 10× genomics platform to generate scRNA-seq libraries. Initial data processing and integration were conducted by CellRanger (v5.0.0). Batch effects were eliminated by harmony (v0.1.0). The Seurat package (v4.0.4) was used to conduct quality control (cells with mitochondrial gene ratio of >15% or genes of <200 were dumped), cell clustering, and differentially expressed gene (DEG) analysis. Genes with adjusted P values of less than 0.05 and | Log2 (fold change) | > 0.25 were identified as DEGs. The transcription factor (TF) activity of Hif1α was calculated by SCENIC (v1.2.2).

The Metascape webtool used the input DEGs to perform GO analysis. We show 5 to 10 GO pathways related to EAU pathogenesis among the top 50 enriched GO pathways.

String was used to construct the protein–protein interaction network based on the up- or down-regulated EAU-associated DEGs. The network was visualized with Cytascape (v3.9.1). Then, the top 10 hub genes were predicted by CytoHubba, a plugin of Cytoscape software.

An EAU model was developed using IRBP1–20, PTX, and CFA. To avoid the nonspecific impacts of the auxiliary agents, an EAU control group was established using only the PTX and CFA. CDLN cells of normal control (NC), EAU control, and EAU groups were isolated for scRNA-seq analysis. After the initial processing and cell clustering, DEGs were identified between the EAU control and NC groups, as well as between EAU and NC groups. Then, the EAU-associated DEGs were identified by excluding DEGs in the EAU control/NC comparison group from the DEGs in the EAU/NC comparison group (Fig. 1A, Supplementary Figs. S1A and B). Eight immune cell clusters were identified: T cells, B cells, NK cells, conventional dendritic cells, plasmacytoid dendritic cells, macrophages, monocytes, and neutrophils (Fig. 1B, Supplementary Figs. S1C–E). To identify the general transcriptional changes, a DEG analysis was conducted on the total CDLN cells, and the up- and down-regulated EAU-associated or non–EAU-associated DEGs were identified (Fig. 1C). We then performed GO analysis to annotate these genes. The genes related to antigen processing and presentation (B2m, H2-DMa, and H2-Oa), immunoglobulin production (Ighg1 and Ighm), and lymphocyte activation (Icos, Jun, and Jund) were included in the up-regulated EAU-associated DEGs (Fig. 1D). These DEGs also enriched in pathways annotated as “lymphocyte activation,” “Th17 cell differentiation,” and “IL-17 signaling pathway” (Fig. 1F). Genes involved in the GO pathway negative regulation of immune system processes (Arrb2, Tgfb1, Gps2, and Ptpn6)– were included in the down-regulated EAU-associated DEGs (Fig. 1D, Supplementary Fig. S1F). Non–EAU-associated DEGs were also identified, and these genes contributed to up-regulated pathways related to inflammation (S100a8, S100a11, and Ccl5), neutrophil degranulation (Ctss, Ctsb, and Lyz2), and regulation of innate immune response (Apoe and Tyrobp), and down-regulated pathway related to mRNA processing (Cirbp, Pcbp1, Rps29, and Hnrnpdl) (Figs. 1E and F, Supplementary Fig. S1F). These results indicated the differences between EAU and non–EAU-associated DEGs. The former mainly showed enhanced lymphocyte activation and differentiation and Th17 cell response, whereas the latter mainly showed an augmented inflammatory and innate immune response to nonspecific adjuvants. Thus, we focused on the EAU-associated DEGs in the subsequent analysis. EAU-associated DEGs of major immune cell types were then identified. Monocytes showed the most EAU-associated DEGs, followed by T and B cells (Supplementary Fig. S1G). In T cells, the up-regulated EAU-associated DEGs contribute to pathways annotated as “cell population proliferation,” “T-cell activation,” “Th17 cell differentiation,” and “IL-17 signaling,” thereby indicating an enhanced Th17 response in EAU (Fig. 1G). The pathways annotated as “immunoglobulin production” and “antigen processing and presentation” were enriched in B cells (Fig. 1G). Conventional dendritic cells and plasmacytoid dendritic cells also exhibited enriched pathway annotated as “antigen processing and presentation” along with pathways related to the regulation of T cell responses (Fig. 1G). Macrophages showed up-regulated pathways related to scavenging, whereas the pathways related to inflammatory responses were up-regulated in the other innate immune cells, especially in monocytes (Fig. 1G). The down-regulated EAU-associated DEGs were enriched in translation initiation complex formation-related pathways in T cells, negative regulation of leukocyte activation-related pathways in B cells, and ribosome-related pathways in innate immune cells (Supplementary Fig. S1H).

T and B cells actively participate in autoimmunity., Eight identifiable subpopulations were identified in T cells: naïve CD8+ T, naïve CD4+ T, T follicular helper, Treg, Th17, Th1, cytotoxic T, and proliferative T cells (Figs. 2A and B, Supplementary Figs. S2A and B). Up-regulated EAU-associated DEGs outnumbered the down-regulated ones in most T-cell subsets (Fig. 2C). GO analysis of the up-regulated EAU-associated DEGs identified enriched pathways related to cell activation, cellular response to stress and stimuli, and cytokine production in most subpopulations of T cells (Fig. 2D). This indicated generally enhanced T-cell activation and cytokine production in EAU. Pathways related to the regulation of adaptive immune responses were enriched in Th1 and Th17 cells, whereas the positive regulation of leukocyte mediated cytotoxicity pathway was uniquely up-regulated in cytotoxic T cells (Fig. 2D). The down-regulated EAU-associated DEGs were enriched in pathways annotated as SRP-dependent co-translational protein targeting to membrane, ribosome, and L13a-mediated translational silencing of ceruloplasmin expression, in most T-cell subpopulations (Fig. 2E). We then reclustered B cells into three identifiable clusters: naïve B cells, germinal center cells, and plasma cells (Fig. 2F, Supplementary Figs. S2C–E). Germinal center cells accounted for the most EAU-associated DEGs (Fig. 2G). GO analysis of the up-regulated EAU-associated DEGs identified enriched pathways in naïve B cells annotated as peptide biosynthetic process and antigen processing and presentation (Fig. 2H). Pathways related to the cellular responses to stimuli and stress were enriched in the germinal center and plasma cells (Fig. 2H). The pathway annotated as cell division was enriched in the germinal center cells (Fig. 2H). These GO terms indicate enhanced antigen processing and presentation capacity, as well as enhanced cell division of B cells in EAU. The down-regulated EAU-associated DEGs contributed to pathways associated with the negative regulation of cell activation in naïve B cells and plasma cells, and pathways related to the ribosome in germinal center cells (Supplementary Fig. S2F).

Th1, Th17, and Treg cells are critical participants in EAU.,, To investigate the potential common regulators of these T-cell subsets, a Venn diagram of their up-regulated EAU-associated DEGs was constructed (Fig. 3A). Thirteen common DEGs were observed (Fig. 3A), among which Hsp90ab1, Hsp90aa1, Hspa8, and S100a13 are related to stress responses and inflammation–; Acot7, Srgn, Tagln2, Fkbp1a, Tigit, and Myl6 are regularly identified in cancer studies–; Bhlhe40 and Id2 regulate cell proliferation and differentiation–; and Hif1α encodes the alpha subunit of Hif1, which regulates cellular responses to hypoxia and actively participates in metabolism, cancer, and immune-related processes.– Similarly, four common down-regulated EAU-associated DEGs were identified: Rpl37a, Eef2, Rps27, and Txnip (Supplementary Fig. S4A). Rpl37a, Eef2, and Rps27 are related to ribosome and protein translation, whereas Txnip regulates glucose homeostasis., To further identify the critical genes involved in EAU, protein–protein interaction networks were constructed for the Th1, Th17, and Treg cells based on the up-regulated and down-regulated EAU-associated DEGs using the STRING database and Cytoscape software (Supplementary Figs. S3, S4B–D). The CytoHubba plug-in for Cytoscape predicted the top 10 hub genes of each subset (Fig. 3B, Supplementary Fig. S4E). Hsp90ab1, Hsp90aa1, and Hif1α were the commonly up-regulated hub genes, whereas Eef2 was the commonly down-regulated hub gene (Fig. 3C, Supplementary Fig. S4F). The results indicate that Hif1α may regulate Th1, Th17, and Treg cells in EAU. During EAU, Hif1α expression was increased evidently in the Th17, Th1, and Treg cells when compared with that in the other T-cell subsets (Figs. 3D, E). Because Hif1α is a TF, SCENIC was used to predict its TF activity. The TF activity of Hif1α in Treg, Th17, and Th1 cells increased during EAU (Fig. 3F). Thus, Hif1α may engage in EAU pathogenesis by regulating Th1, Th17, and Treg cells.

To validate the role of Hif1α in EAU, EAU mice were treated with an Hif1α inhibitor, KC7F2., The KC7F2 treatment decreased the retinal lesions, infiltrations, and folding in EAU mice, and both the clinical and pathological scores were lower (Figs. 4A–D). Ocular-infiltrating CD4+ T cells dominate in EAU pathogenesis. The KC7F2 treatment reduced the infiltration of CD4+ IL17A+ T and CD4+ IFN-γ T cells into the mice retina (Figs. 4E–G). In the CDLNs cells, the KC7F2 treatment decreased the proportion of CD4+ IL17A+T and CD4+ IFN-γ+ T cells, whereas treatment increased that of CD4+ Foxp3+ T cells (Figs. 4I–K). These results revealed the pathogenic role of Hif1α in EAU. Inhibition of Hif1α ameliorated EAU symptoms and restored the Teff/Treg balance during EAU.

In vitro experiments were conducted to further explore the functions of Hif1α. Cells from the CDLNs were isolated and treated with KC7F2. Similar to the in vivo experiments, KC7F2 treatment decreased the proportion of CD4+ IL17A+ T and CD4+ IFN-γ+ T cells, but increased the proportion of CD4+ Foxp3+ T cells (Figs. 5A–F). To explore the contribution of Hif1α expression in the EAU-induction function of CD4+ T cells, CD4+ T cells from EAU mice treated or not with KC7F2 were adoptive transferred into naïve mice. The KC7F2-treated CD4+ T cells lost their capacity to induce EAU in naïve mice (Figs. 5G–J). This result indicates that Hif1α expression is indispensable for CD4+ T cells to induce EAU.

To explore whether, in human uveitis Hif1α expression was also enhanced in CD4+ T cells, scRNA-seq analysis was performed on peripheral blood mononuclear cells of five healthy controls and five patients with VKH disease. Six known cell clusters were identified: B cells, T cells, DC, monocytes, NK cells, and plasma cell (Figs. 6A and B, Supplementary Figs. S5A and B). The T cells were subdivided into CD8+ naïve T (CD8+ naïve), CD4+ naïve T (CD4+ naïve), CD4+ Treg, CD4+ central memory T (CD4+ Tcm), CD4+ effector memory T (CD4+ Tem), CD8+ Tem, and CD8+ cytotoxic T cells (CD8+ cytotoxic T cells, Figs. 6C–E, Supplementary Fig. S5B). The CD4+ T-cell subsets from patients with VKH disease exhibited increased Hif1α expression when compared with those from healthy controls (Fig. 6F). Flow cytometry results also showed the increased Hif1α expression in CD4+ T cell in VKH disease at the protein level (Fig. 6G). In addition, the inhibition of Hif1α repressed the CD4+ T-cell proliferation (Fig. 6H). Therefore, the enhanced Hif1α expression in CD4+ T cells was conserved in VKH disease and Hif1α may be a possible therapeutic target for this disease.

Here, the pathogenesis of AU was explored from the perspective of EAU-associated DEGs. Hif1α was identified as an up-regulated EAU-associated DEG in Th1, Th17, and Treg cells. Inhibition of Hif1α ameliorated EAU symptoms and regressed retinal infiltration of Th17 and Th1 cells. Both in vivo and in vitro, Hif1α inhibition decreased Th17 and Th1 cell proportion, but increased Treg cells. Hif1α inhibitor-treated CD4+ T cells lost their EAU-induction capacity. Additionally, in human uveitis, the enhanced Hif1α expression in CD4+ T cells was conserved and may promote their proliferation. Therefore, our experiments suggested that Hif1α participates in uveitis pathogenesis via regulating Teff and Treg cells and may be a potential target for AU therapy. Adjuvants like PTX and CFA are used to enhance the induction of various autoimmune diseases in animal models.,, However, their multifaceted effects on immune responses may hinder the interpretation of experimental data., In our study, the non–EAU-associated DEGs were induced by adjuvants. These DEGs were mainly related to inflammation and stimulus–response, indicating that PTX and CFA induced a nonspecific inflammatory response during EAU. In contrast, the EAU-associated DEGs indicated enhanced lymphocyte activation and differentiation, Th17 cell response, and immunoglobulin production, which are well-known to participate in autoimmune disease pathogenesis., Multiple immune cells are involved in EAU pathogenesis. This study provided insights into their respective responses during EAU. T cells showed enhanced proliferation, activation, IL-17 signaling, and Th17 cell differentiation pathways, whereas B cells showed enhanced immunoglobulin production pathway. DCs showed enhanced antigen processing and presentation and T-cell regulation–related pathways. The other innate immune cells showed enhanced inflammation-related pathways. These transcriptional data were mostly in line with their previously reported functions in uveitis and other autoimmune diseases.,,, For the cell subsets, GO analysis indicated generally enhanced cell activation in T-cell subsets and enhanced antigen presentation and cell division in B-cell subsets. Among the multiple immune cells, Th1, Th17, and Treg cells have long been considered the core participants in uveitis and other autoimmune diseases.,, In our data, Hif1α was the common EAU-associated DEG and predicted hub gene of these T-cell subsets. The bioinformatics analysis indicated that Hif1α may be a regulator of Th1, Th17, and Tregs during EAU. Hif1α has been explored widely in cancer, immunity, angiogenesis, and metabolism.,, Its inhibitor has also been considered a potential therapeutic choice for several diseases, including multiple types of tumors, retinal neovascularization, and rheumatoid arthritis.,, However, whether and how Hif1α plays a role in AU and if Hif1α inhibitor can be a potential therapeutic choice for AU was previously unclear. The imbalance in the Teff and Treg cells is the core pathogenic mechanism of AU and several other autoimmune diseases., A previous study has reported that Hif1α enhanced Th17 cell development via the direct transcriptional activation of its core TF, RORγt, and attenuated Treg cell development by binding Foxp3 to target it for proteasomal degradation. Whether the regulatory role of Hif1α on Teff and Treg cells exists in uveitis is unclear. Our results showed that Hif1α inhibition ameliorated EAU symptoms and decreased the retinal infiltration of Teff cells. Additionally, the inhibitor of Hif1α reduced Teff cell proportion, but increased Treg cells in CDLN cells. These results indicate that Hif1α may disturb the balance of Teff and Treg cells and promote EAU. Hif1α was also reported to regulate other immune cells, including macrophages and neutrophils. The wide regulatory function of Hif1α may complicate the interpretation of experimental results using Hif1α inhibitors. Our study conducted a CD4+ T-cell adoptive transfer experiment and showed that Hif1α is necessary for CD4+ T cells to induce EAU. Additionally, in peripheral blood mononuclear cells from patients with VKH disease, we also observed enhanced Hif1α expression in CD4+ T cells at both mRNA and protein levels. Hif1α inhibition could regress human CD4+ T-cell proliferation. These results further suggest that Hif1α may be a possible target for AU therapy. This study successfully applied scRNA-seq and flow cytometry to unravel Hif1α as a potential pathogenic molecule in uveitis at the transcriptional and protein levels. Experiments based on patient samples further expanded the possibility of Hif1α as a therapeutic target of uveitis. Some potential limitations also existed. Regulatory B cells and some myeloid cell subpopulations such as M1 macrophages and C1q high monocytes were involved in uveitis progress or inhibition.– However, owing to their small number, they cannot be identified and clustered separately in our scRNA-seq data. For these cells, sorting and enrichment through flow cytometry before conducting scRNA-seq was required. In addition, uveitis encompassed many types such as Behçet disease and idiopathic uveitis. Owing to the relatively low morbidity of uveitis, our study did not include samples from patients with all types of uveitis but choose VKH disease, a relatively common type of human uveitis in Asia. Overall, this study showed the EAU-associated transcriptional changes in each cell type and indicated that Hif1α may be an active participant in EAU pathogenesis by mediating the Teff and Treg imbalance. Inhibition of Hif1α could restore the balance of Teff and Treg and ameliorate EAU. Higher expression levels of Hif1α in the CD4+ T cells was conserved in human uveitis, further indicating that Hif1α may be a potential therapeutic target for this disease.