Erratum: Distinct HLA Associations with Rheumatoid Arthritis Subsets Defined by Serological Subphenotype (The American Journal of Human Genetics (2019) 105(3) (616–624), (S0002929719303052), (10.1016/j.ajhg.2019.08.002))

© 2019 The Author(s) (The American Journal of Human Genetics 105, 616–624; September 5, 2019) In the originally published version of this article, the first author, Chikashi Tereo, had footnotes indicating affiliations with the first seven institutions. The correct affiliations are the first six plus footnote 17, indicating equal contribution. This error has been corrected here and online, and the authors and copyeditor express their regret for the mistake

IMECE2008-67360 GASTROESOPHAGEAL REFLUX 2D AND 3D STEADY STATE CFD SIMULATIONS

ABSTRACT Gastro-Esophageal Reflux Disease (GERD) is a condition which affects up to 20% of the adult US population on a weekly basis. It is a condition where acid is allowed to flow from the stomach and into the esophagus where it causes damage to the local tissue. In chronic cases the condition can lead to cancer. Dysfunction of the Esophagogastric Junction is indicated as a primary cause. The recently developed Functional Lumen Imaging Probe (FLIP) is designed for assessment of the EGJ. It measures the cross sectional area at eight locations through the junction. This data has been used to construct a series of computational fluid dynamic simulations. These simulations showed a jet of fluid which squirts into the esophagus under the gastric pressure. This jet corresponds with previously gathered anecdotal evidence. The centerline velocities of this jet were measured and this suggested that the jet could travel up to 20 times the minimum diameter of the EGJ into the esophagus before decelerating to 25% of its original velocity. This means that if an EGJ was curved then this jet could impinge on the walls causing a localized area of increased damage to the mucosa compared to the surrounding tissue

Correlation between depression and burden observed in informal caregivers of people suffering from dementia with time spent on caregiving and dementia severity

[Abstract] OBJECTIVE: The aim of the study is to compare data on the examined population of informal caregivers of people suffering from dementia with previous studies, as well as to assess the correlation between (i) depression determined on the basis of the Center for Epidemiologic Studies Depression Scale and (ii) caregiver burden measured by means of the Zarit Caregiver Burden Scale and some chosen parameters, such as total time devoted to caregiving, time of caregiving in hours per week and level of dementia severity measured by Global Deterioration Scale. PATIENTS AND METHODS: 41 informal caregivers of people suffering from dementia from different backgrounds were evaluated using the Zarit Caregiver Burden Scale and the Center for Epidemiologic Studies Depression Scale. Demographic data about the time devoted to caregiving and the number of hours spend on caregiving weekly were gathered. The type of dementia and its stage were registered using the Global Deterioration Scale (GDS). With the aid of the Statistica StatSoft program, mutual correlations between the parameters were measured. The study was conducted within the framework of AAL UnderstAID – a platform that supports and helps to understand and assist caregivers in the care of a relative with dementia. The international project is co-founded by the Joint Programme Ambient Assisted Living (Grant code: ESR-aal 2012 5 107). RESULTS: No significant correlations between the level of depression severity evaluated in caregivers and the total time of taking care of a demented person or time of caregiving in hours per week were observed. Similarly, no significant correlation between depression severity level and dementia severity level measured on the GDS scale were noted. There was also no significant correlation between Zarit Caregiver Burden Scale scores and the above-mentioned parameters. CONCLUSIONS: The level of depression among caregivers do not depend on socio-demographic factors

Defining inflammatory cell states in rheumatoid arthritis joint synovial tissues by integrating single-cell transcriptomics and mass cytometry

© 2019, The Author(s), under exclusive licence to Springer Nature America, Inc. To define the cell populations that drive joint inflammation in rheumatoid arthritis (RA), we applied single-cell RNA sequencing (scRNA-seq), mass cytometry, bulk RNA sequencing (RNA-seq) and flow cytometry to T cells, B cells, monocytes, and fibroblasts from 51 samples of synovial tissue from patients with RA or osteoarthritis (OA). Utilizing an integrated strategy based on canonical correlation analysis of 5,265 scRNA-seq profiles, we identified 18 unique cell populations. Combining mass cytometry and transcriptomics revealed cell states expanded in RA synovia: THY1(CD90) + HLA-DRA hi sublining fibroblasts, IL1B + pro-inflammatory monocytes, ITGAX + TBX21 + autoimmune-associated B cells and PDCD1 + peripheral helper T (T PH ) cells and follicular helper T (T FH ) cells. We defined distinct subsets of CD8 + T cells characterized by GZMK + , GZMB + , and GNLY + phenotypes. We mapped inflammatory mediators to their source cell populations; for example, we attributed IL6 expression to THY1 + HLA-DRA hi fibroblasts and IL1B production to pro-inflammatory monocytes. These populations are potentially key mediators of RA pathogenesis

Methods for high-dimensonal analysis of cells dissociated from cyropreserved synovial tissue

© 2018 The Author(s). Background: Detailed molecular analyses of cells from rheumatoid arthritis (RA) synovium hold promise in identifying cellular phenotypes that drive tissue pathology and joint damage. The Accelerating Medicines Partnership RA/SLE Network aims to deconstruct autoimmune pathology by examining cells within target tissues through multiple high-dimensional assays. Robust standardized protocols need to be developed before cellular phenotypes at a single cell level can be effectively compared across patient samples. Methods: Multiple clinical sites collected cryopreserved synovial tissue fragments from arthroplasty and synovial biopsy in a 10% DMSO solution. Mechanical and enzymatic dissociation parameters were optimized for viable cell extraction and surface protein preservation for cell sorting and mass cytometry, as well as for reproducibility in RNA sequencing (RNA-seq). Cryopreserved synovial samples were collectively analyzed at a central processing site by a custom-designed and validated 35-marker mass cytometry panel. In parallel, each sample was flow sorted into fibroblast, T-cell, B-cell, and macrophage suspensions for bulk population RNA-seq and plate-based single-cell CEL-Seq2 RNA-seq. Results: Upon dissociation, cryopreserved synovial tissue fragments yielded a high frequency of viable cells, comparable to samples undergoing immediate processing. Optimization of synovial tissue dissociation across six clinical collection sites with ~ 30 arthroplasty and ~ 20 biopsy samples yielded a consensus digestion protocol using 100 μg/ml of Liberase™ TL enzyme preparation. This protocol yielded immune and stromal cell lineages with preserved surface markers and minimized variability across replicate RNA-seq transcriptomes. Mass cytometry analysis of cells from cryopreserved synovium distinguished diverse fibroblast phenotypes, distinct populations of memory B cells and antibody-secreting cells, and multiple CD4+ and CD8+ T-cell activation states. Bulk RNA-seq of sorted cell populations demonstrated robust separation of synovial lymphocytes, fibroblasts, and macrophages. Single-cell RNA-seq produced transcriptomes of over 1000 genes/cell, including transcripts encoding characteristic lineage markers identified. Conclusions: We have established a robust protocol to acquire viable cells from cryopreserved synovial tissue with intact transcriptomes and cell surface phenotypes. A centralized pipeline to generate multiple high-dimensional analyses of synovial tissue samples collected across a collaborative network was developed. Integrated analysis of such datasets from large patient cohorts may help define molecular heterogeneity within RA pathology and identify new therapeutic targets and biomarkers

TYK2 protein-coding variants protect against rheumatoid arthritis and autoimmunity, with no evidence of major pleiotropic effects on non-autoimmune complex traits

Despite the success of genome-wide association studies (GWAS) in detecting a large number of loci for complex phenotypes such as rheumatoid arthritis (RA) susceptibility, the lack of information on the causal genes leaves important challenges to interpret GWAS results in the context of the disease biology. Here, we genetically fine-map the RA risk locus at 19p13 to define causal variants, and explore the pleiotropic effects of these same variants in other complex traits. First, we combined Immunochip dense genotyping (n = 23,092 case/control samples), Exomechip genotyping (n = 18,409 case/control samples) and targeted exon-sequencing (n = 2,236 case/controls samples) to demonstrate that three protein-coding variants in TYK2 (tyrosine kinase 2) independently protect against RA: P1104A (rs34536443, OR = 0.66, P = 2.3 x 10(-21)), A928V (rs35018800, OR = 0.53, P = 1.2 x 10(-9)), and I684S (rs12720356, OR = 0.86, P = 4.6 x 10(-7)). Second, we show that the same three TYK2 variants protect against systemic lupus erythematosus (SLE, Pomnibus = 6 x 10(-18)), and provide suggestive evidence that two of the TYK2 variants (P1104A and A928V) may also protect against inflammatory bowel disease (IBD; P(omnibus) = 0.005). Finally, in a phenome-wide association study (PheWAS) assessing \u3e500 phenotypes using electronic medical records (EMR) in \u3e29,000 subjects, we found no convincing evidence for association of P1104A and A928V with complex phenotypes other than autoimmune diseases such as RA, SLE and IBD. Together, our results demonstrate the role of TYK2 in the pathogenesis of RA, SLE and IBD, and provide supporting evidence for TYK2 as a promising drug target for the treatment of autoimmune diseases