Immune cell parameters found to be impacted in patients with autoimmune and autoinflammatory disorders enrolled in the Transimmunom study.

Expanding upon the Transimmunom clinical trial, we gathered peripheral blood samples from 443 patients enrolled between 2015 and 2022, who were afflicted with 15 distinct autoimmune or autoinflammatory diseases or related conditions. Additionally, blood samples were collected from 71 healthy volunteers to establish a reference condition. The screened disorders spanned a spectrum from purely autoinflammatory to purely autoimmune diseases, encompassing various levels of disorder activities without a specific threshold. The disorders examined included arthritis conditions such as Behçet's disease (BD; n=38), knee osteoarthritis (OA; n=45), rheumatoid arthritis (RA; n=91), spondylarthritis (SA; n=58), and systemic lupus erythematosus (SLE; n=33). Blood vessel disorders, such as Antiphospholipid syndrome (APLS; n=23), Churg-Strauss's disease (CS; n=6), Granulomatosis with polyangiitis (GPA; n=14), and Takayasu arteritis (TA; n=22), were also included. Metabolic disorders like Type 1 Diabetes (T1D; n=60) and Type 2 Diabetes (T2D; n=27), muscle disorder (Myositis; n=4), inflammatory bowel diseases (IBD) like Crohn's disease (CD; n=10) and ulcerative colitis (UC; n=5), as well as IBD-like diseases including Familial Mediterranean Fever (FMF; n=7), were part of the study.
To analyze the patient blood samples, we utilized 12 flow cytometry panels, each consisting of 10 cell markers. We introduced an extra panel specifically designed to identify the primary immune cell populations. This panel featured numeration beads, enabling the determination of absolute counts for all populations. It served as a reference tube, facilitating the calculation of absolute counts in all other panels through extrapolation from shared populations. In total, we analyzed more than 600 innate and adaptive immune cell parameters (both absolute cell counts and percentages) from patient's blood.
The provided data encompasses significant flow cytometry data related to the Transimmunom study. This dataset specifically details the values of 224 cell parameters that exhibit significant differential abundance in at least one disease when compared to samples from healthy volunteers. Both Cliff's Delta effect size and two-way non-parametric Wilcoxon test were used to identify cell parameters significantly differentially abundant between conditions. Cell parameters with an absolute value of Cliff's Delta effect size higher than 0.33 and with a p-value lower than 0.05 were considered statistically significant. 
The provided file is formatted as a tab-separated file. Each row corresponds to a specific cell parameter, either representing cell percentage or absolute cell count. Each column corresponds to a distinct patient, identified by the disease name and anonymous identifier.