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Linkage disequilibrium poses a major challenge to the functional characterization of specific disease-associated susceptibility variants. Precision genome-editing technologies have provided new opportunities to address this challenge. As proof of concept, we employed TALEN (transcription activation-like effector nuclease)-mediated genome editing to specifically disrupt the TT>A enhancer region to mimic candidate causal variants identified in the systemic lupus erythematosus-associated susceptibility gene, tumor necrosis factor-α-induced protein 3 ( TNFAIP3 ), in an isogenic HEK293T cell line devoid of other linkage disequilibrium-associated variants. Targeted disruption of the TT>A enhancer impaired its interaction with the TNFAIP3 promoter by long-range DNA looping, thereby reducing TNFAIP3 gene expression. Loss of TNFAIP3 mRNA and its encoded protein, A20, impaired tumor necrosis factor-α-induced receptor-mediated downregulation of nuclear factor-κB signaling, a hallmark of autoimmunity. Results demonstrate that the TT>A enhancer variants contribute to causality and function independently of other variants to disrupt TNFAIP3 expression. Furthermore, we believe this approach can be implemented to independently examine other candidate casual variants in the future.

Background:10X Visium spatial transcriptomics evaluates mRNA-binding tiles (55μm diameter) of a sectioned tissue, yielding heterogeneous cell sampling. The SpatialPCA algorithm was developed to identify like tissue regions and determine the cellular context of spatial coordinates using homogenous tissue types with distinct boundaries [1] However, while proficient in analyzing homogenous tissue types, SpatialPCA is less effective at differentiating like tiles from heterogenous tissue types.Objectives:To develop a novel analysis pipeline, HistoSpatialPCA, that leverages spatially aware dimensional reduction to model spatially correlated structures across tiles from heterogeneous tissue types such as a target tissue of Sjögren’s Disease (SjD), the minor salivary gland (MSG). Then, to apply HistoSpatialPCA to MSGs biopsied from SjD patients and healthy controls (HC) to identify disease-specific differential gene expression (DE) and pathway dysregulation in the salivary gland.Methods:MSG sections were arranged on 10X Visium capture slide chambers. Nuclei segmentation and classification was performed, followed by images annotation by tissue type (fibrosis, glandular, inflammatory, fat) (HALO Image Analysis Platform). Imaging data were extracted from tiles and integrated with spatial coordinates using HistoPCA. After quality control to filter low-quality and non-tissue tiles, SpatialPCA was performed [1]. Subsequently, data integration (Harmony) and UMAP with KMeans clustering were performed. SjD case-control differential expression (DE) was analyzed using pseudo-bulk gene expression. Finally, DE transcripts were analyzed by Ingenuity Pathway Analysis.Results:HistoSpatialPCA, followed by UMAP with KMeans clustering, detected 34,948 tiles from n=41 subjects, resulting in 8 distinct clusters in the MSG (Figure 1A,B). Comparison of dysregulated genes and pathways revealed cluster-specific differences between Ro+ and Ro- SjD cases verses HCs (Figure 1C). Ro+ SjD cases exhibited dysregulation across all clusters, whereas Ro- cases showed no significant dysregulated pathways in clusters 0, 2, and 7 and fewer altered pathways in clusters 1 and 6. Rank order of the dysregulated pathways also differed between Ro+ and Ro- SjD cases. Interferon gamma was the top pathway in all SjD cases and Ro+ across all clusters, but was only dysregulated in Ro- cluster 5 and modestly in clusters 1 and 3. Cluster 5 was the most similar between Ro+ and Ro- and showed the highest percentage of inflammation (upregulation of many proinflammatory pathways; downregulation of CTLA4, IL-10, and PD-1 signaling).Conclusion:HistoSpatialPCA successfully grouped like tiles from spatial transcriptomic analysis of heterogeneous MSG. Cluster annotation, followed by DE and pathway analyses revealed dysregulation of tiles across all clusters in Ro+ SjD cases, while Ro- cases exhibited the most pronounced dysregulation in cluster 5, 4, and 3. Notably, cluster 5 demonstrated the highest inflammation, sharing many dysregulated pathways between Ro+ and Ro- SjD cases. This spatially aware technology will provide new insights into the role of different cell/tissue types in SjD pathobiology of the salivary gland.REFERENCES:[1] Shang L, et al. Nat Commun. 2022; 13:7203.Acknowledgements:National Institutes of Health (NIH): R01ARO7385503 (CJL); R21 DE029302 (ADF).Disclosure of Interests:Songyuan Yao: None declared, Rick Wilbrink: None declared, Paulina Czarnota: None declared, Matthew Caleb Marlin: None declared, Bhuwan Khatri: None declared, Anna M Stolarczyk: None declared, Cherilyn Pritchett Frazee: None declared, Chuang Li: None declared, Kyle Wright: None declared, Kandice L Tessneer: None declared, Judith A. James: None declared, R Hal Scofield Received consulting fees from Johnson and Johnson Innovative Medicine (formerly Janssen) and Merk Pharmaceuticals., Indra Adrianto: None declared, Astrid Rasmussen: None declared, Joel M Guthridge: None declared, A Darise Farris Grant/research support from Johnson and Johnson Innovative Medicine (formerly Janssen; ended 12/31/23)., Christopher J Lessard Grant/research support from Johnson and Johnson Innovative Medicine (formerly Janssen; ended 12/31/23).

Background:SjD is a chronic, heterogeneous autoimmune disease characterized by signs of oral and ocular dryness in patients who are either positive for anti-Ro/SSA and/or focus score positive on biopsies from labial/parotid salivary glands. Although involvement of salivary glands is a distinguishing disease feature, little is known about the transcriptomics of discrete cell populations in the glands.Objectives:To determine the optimal dissociation approach and single-cell (sc) transcriptomics platform for the use of matched viably frozen and fixed minor salivary glands (MSG) biopsied from SjD patients and healthy controls (HCs); then, to expand the dataset using the optimal approach.Methods:Viably frozen MSG (n=7; 2 SjD and 5 HCs) were thawed, dissociated, and counted, showing >90% viable cells. Samples were split and captured using 3’ and 5’ scRNA-seq, targeting to capture 8000-10000 cells. In addition, 25μm sections from formalin-fixed paraffin-embedded (FFPE) tissues containing 4-5 labial salivary glands (LSG) each were dissociated, counted, labeled following the 10X Flex/scFFPE protocol, and captured, yielding 8000-20000 cells per subject. Raw sequencing data were analyzed using 3’, 5’, or scFFPE analysis pipelines in CellRanger. Ambient RNAs were corrected (SoupX) and doublets detected (scDblfinder). Cells with feature counts <200 & >5000, mitochondrial percent >5%, and doublets were removed. Samples were merged, integrated, and batch corrected using Harmony (Seurat). Data were normalized, scaled, and dimensional reduction performed using UMAP (Seurat). Cell clusters were annotated using CellTypist and MSG reference data1. Cells were separated into immune and non-immune clusters and annotated using reference data from CellTypist or MSG reference data1. Differentially expressed (DE) genes in each cell type in SjD compared to HC were identified using pseudobulk approach (DESeq2). DE genes (p<0.05) were subjected to Ingenuity Pathway Analysis (IPA).Results:Overall quality of the 3’ and 5’ approaches were similar. In comparison, scFFPE yielded similar feature/gene counts per cell (median = 5186 (3’), 7452 (5’), 4571 (scFFPE)), but was superior in the reduction of ambient RNA (or soup) and in identifying cell populations that were very low in 3’ and 5’ assays: seromucous acini, basal cells, macrophages, myoepithelial cells, among others. The scFFPE dataset was expanded to include 8 Ro+ SjD and 9 HCs, yielding 477,071 cells before QC, 371,454 after QC, among 23 cell states (Figure 1A). It revealed significantly DE genes in Ro+ SjD compared to HCs that mapped to common and different pathways between immune (Figure 1B and C) and glandular cells (Figure 1B and D). For example, many cell types showed dysregulation of Type I interferon, including downregulation (plasma cells, plasmacytoid DCs, naive B cells), upregulation (migratory DCs, DC1, serous and mucus acini, macrophages, mast cells), or no dysregulation (DC2, memory B, cytotoxic T, helper T, and natural killer cells).Conclusion:scFFPE yielded superior single-cell data compared to 3’ and 5’ using viable cells. Further, the data analysis method permitted discrimination of targeted/affected cell types from effector cell types. Expansion of the scFFPE pilot study showed many DE genes and dysregulated pathways. Ongoing work with AMP-AIM STAMP projects will further expand this dataset.REFERENCES:[1] Huang N, et al. SARS-CoV-2 infection of the oral cavity and saliva. Nat Med. 2021 May; 27(5):892-903.Acknowledgements:National Institutes of Health: UM2 AR067678, UC2 AR081023, UC2 AR081032, UC2 AR081032-S1, UC2 AR081032-02S1, UC2 DE032254, UC2 AR081033, P30 AR073750, U54 GM104938, NIDCR 15-D-0051; Presbyterian Health Foundation; OMRF Institutional Funds; NIH, NCI Intramural Program; Jerome L. Greene Foundation.Disclosure of Interests:Bhuwan Khatri: None declared, Anna M Stolarczyk: None declared, Matthew Caleb Marlin: None declared, Miles Smith: None declared, Cherilyn Pritchett Frazee: None declared, Margaret Beach: None declared, Eileen Pelayo: None declared, Zohreh Khavandgar: None declared, Paola Pérez: None declared, David E Kleiner: None declared, Stephen E Hewitt: None declared, Kevin Wei Received a sponsored research agreement from Gilead Sciences and 10X Genomics., Erin M Theisen: None declared, Kandice L Tessneer: None declared, Soumya Raychaudhuri: None declared, Michael B Brenner: None declared, Johann E. Gudjonsson: None declared, Nir Hacohen: None declared, Judith A. James: None declared, R Hal Scofield Received consulting fees from Johnson and Johnson Innovative Medicine (formerly Janssen) and Merk Pharmaceuticals., Stephen Shiboski: None declared, Astrid Rasmussen: None declared, Alan Baer Received consulting fees from Bristol Myers Squibb (BMS) and iCell Gene Therapeutics., A Darise Farris Grant/research support from Johnson and Johnson Innovative Medicine (formerly Janssen; ended 12/31/2023)., Caroline Shiboski: None declared, Blake M Warner Receives funding to support research from Pfizer, Inc., and Mitobridge, Inc., a subsidiary of Astellas Bio., Joel M Guthridge: None declared, Christopher J Lessard Grant/research support from Johnson and Johnson Innovative Medicine (formerly Janssen; ended 12/31/2023).

Background:Sjögren’s disease (SjD) is a complex systemic autoimmune disease with substantial morbidity and 21 known genetic associations. The International Sjögren’s Genetics Network (SGENE) is a growing international collaboration focused on understanding how genetic variants influence SjD pathology. As sample sizes increase, we are focusing our efforts on the analyses of clinical subsets, which few studies have done.Objectives:Our genome-wide association study (GWAS) aimed to identify additional risk loci of genome-wide significance (GWS, p<5E-08; suggestive, p<5x10E-5) in European-derived subsets of SjD.Methods:This study was conducted with IRB/EC approvals. All SjD patients met the 2002 AECG criteria for SjD. A total of 5058 cases and 25943 controls were genotyped on GWAS arrays. After QC, 4855 cases and 25408 controls were included in the analyses. Logistic regression was calculated, adjusting for ancestry using the first 4 principal components to identify SjD-associated SNPs. Cases were split into Ro/SSA+ (n=2898) and Ro/SSA- (n=1313), and analyzed vs. each other, controls, and all-SjD.Results:We observed many differences in the genomic architecture of Ro/SSA- compared to Ro/SSA+ and all SjD (Figure 1a,b), most notably, a complete loss of the significance of the association with MHC on chromosome 6 in the Ro/SSA- cases(Figure 1b). The Ro/SSA+ subjects had a much stronger HLA association with OR ≈ 4 (Figure 1a), while the overall SjD showed OR ≈ 3. While none of the associations observed in the Ro/SSA- population reached GWS, 8 regions (near PLXNA2, PCDH7, IRF5-TNPO3, DLD, LOC100134229, JAK3, LOC643529, and TMTC1) show suggestive associations (Figure. 1a). Of these, only two, IRF5-TNPO3 and LOC643529, are also suggestive in the Ro/SSA+ subset. However, while the Ro/SSA+ have both the IRF5 promoter effect and the extended haplotype through TNPO3, the Ro/SSA- lack the IRF5 promoter effect. Interestingly, previous studies have shown that lupus and systemic sclerosis have both haplotypes while primary biliary cholangitis only has the haplotype extending into TNPO3, similar to Ro/SSA- SjD [1]. When comparing Ro/SSA- to the all-SjD dataset, PLXNA2 and LOC100134229 showed no association; PCDH7, DLD, and TMTC1 showed some association but did not reach suggestive levels; and LOC643529, IRF5-TNPO3, and JAK3 surpassed the suggestive threshold, the latter two nearing or surpassing GWS. Two of the novel suggestive associations in Ro/SSA- are particularly intriguing. PLXNA2 is a member of a semaphorin co-receptor family that mediates repulsive effects on axon pathfinding during nervous system development; interestingly, Ro/SSA- SjD has a higher frequency of neurological involvement. JAK3 is a member of the Janus kinase (JAK) family of tyrosine kinases involved in cytokine receptor-mediated intracellular signal transduction; it is predominantly expressed in immune cells. Mutations in this gene are associated with autosomal severe combined immunodeficiency disease. Novel drugs target the JAK-STAT pathways, making this finding markedly relevant.Conclusion:Our findings highlight the relevance of expanding genetic studies to specific subphenotypes of the disease. While we continue to increase our GWAS sample size and explore other subphenotypes, more work is needed to increase the power of these studies to determine if the suggestive regions will surpass the GWS threshold.REFERENCES:[1] Kottyan LC, et al. Hum Mol Genet. 2015 Jan 15;24(2):582-96.Acknowledgements:NIH/NIAMS R01 AR073855, P50 AR060804; NIH/NIDCR U01DE028891; Sjögren’s Foundation; Jerome L. Greene Foundation.Disclosure of Interests:Astrid Rasmussen: None declared, Marcin Radziszewski: None declared, Bhuwan Khatri: None declared, Kandice L Tessneer: None declared, Elena Pontarini: None declared, Michele Bombardieri: None declared, Maureen Rischmueller: None declared, Marie Wahren-Herlenius: None declared, Marika Kvarnström: None declared, Torsten Witte: None declared, Hendrika Bootsma: None declared, Gwenny M. Verstappen: None declared, Frans G.M. Kroese: None declared, Arjan Vissink: None declared, Sarah Pringle: None declared, Athanasios Tzioufas: None declared, Clio Mavragani: None declared, Alan Baer Received consulting fees from Bristol Myers Squibb (BMS) and iCell Gene Therapeutics., Marta Alarcon-Riquelme: None declared, Javier Martin: None declared, Xavier Mariette: None declared, Gaetane Nocturne: None declared, Jacques-Olivier Pers: None declared, Jacques-Eric Gottenberg: None declared, Wan-Fai Ng I have consulted for Novartis, BMS, Janssen, Sanofi, Abbvie, IQVIA, Argenx, Resolve Therapeutics., Caroline Shiboski: None declared, Kimberly E Taylor: None declared, Lindsey Criswell: None declared, Blake M Warner: None declared, A Darise Farris Grant/research support from Johnson and Johnson Innovative Medicine (formerly Janssen; ended 12/31/2023)., Judith A. James: None declared, R Hal Scofield Received consulting fees from Johnson and Johnson Innovative Medicine (formerly Janssen) and Merk Pharmaceuticals., Joel M Guthridge: None declared, Daniel J Wallace: None declared, Swamy Venuturupali: None declared, Michael T Brennan: None declared, Juliana Imgenberg-Kreuz: None declared, Lars Ronnblom: None declared, Eva Baecklund: None declared, Maija-leena Eloranta: None declared, Lara A Aqrawi: None declared, Øyvind Palm: None declared, Johan G Brun: None declared, Daniel Hammenfors: None declared, Malin V Jonsson: None declared, Silke Appel: None declared, Sara Magnusson Bucher: None declared, Helena Forsblad-d’Elia: None declared, Thomas Mandl Employee of UCB., Per Eriksson: None declared, Gunnel Nordmark: None declared, Christopher J Lessard Grant/research support from Johnson and Johnson Innovative Medicine (formerly Janssen; ended 12/31/2023).