Susceptibility to childhood-onset rheumatoid arthritis: investigation of a weighted genetic risk score that integrates cumulative effects of variants at five genetic loci.

OBJECTIVE: Children with childhood-onset rheumatoid arthritis (RA) include those with rheumatoid factor or anti-citrullinated protein antibody-positive juvenile idiopathic arthritis. To test the hypothesis that adult-onset RA-associated variants are also associated with childhood-onset RA, we investigated RA-associated variants at 5 loci in a cohort of patients with childhood-onset RA. We also assessed the cumulative association of these variants in susceptibility to childhood-onset RA using a weighted genetic risk score (wGRS). METHODS: A total of 155 children with childhood-onset RA and 684 healthy controls were genotyped for 5 variants in the PTPN22, TRAF1/C5, STAT4, and TNFAIP3 loci. High-resolution HLA-DRB1 genotypes were available for 149 cases and 373 controls. We tested each locus for association with childhood-onset RA via logistic regression. We also computed a wGRS for each subject, with weights based on the natural log of the published odds ratios (ORs) for the alleles investigated, and used logistic regression to test the wGRS for association with childhood-onset RA. RESULTS: Childhood-onset RA was associated with TNFAIP3 rs10499194 (OR 0.60 [95% confidence interval 0.44-0.83]), PTPN22 rs2476601 (OR 1.61 [95% confidence interval 1.11-2.31]), and STAT4 rs7574865 (OR 1.41 [95% confidence interval 1.06-1.87]) variants. The wGRS was significantly different between cases and controls (P < 2 × 10(-16) ). Individuals in the third to fifth quintiles of wGRS had a significantly increased disease risk compared to baseline (individuals in the first quintile). Higher wGRS was associated with increased risk of childhood-onset RA, especially among males. CONCLUSION: The magnitude and direction of the association between TNFAIP3, STAT4, and PTPN22 variants and childhood-onset RA are similar to those observed in RA, suggesting that adult-onset RA and childhood-onset RA share common genetic risk factors. Using a wGRS, we have demonstrated the cumulative association of RA-associated variants with susceptibility to childhood-onset RA.

Immune determinants of CAR-T cell expansion in solid tumor patients receiving GD2 CAR-T cell therapy.

Chimeric antigen receptor T cells (CAR-Ts) have remarkable efficacy in liquid tumors, but limited responses in solid tumors. We conducted a Phase I trial (NCT02107963) of GD2 CAR-Ts (GD2-CAR.OX40.28.z.iC9), demonstrating feasibility and safety of administration in children and young adults with osteosarcoma and neuroblastoma. Since CAR-T efficacy requires adequate CAR-T expansion, patients were grouped into good or poor expanders across dose levels. Patient samples were evaluated by multi-dimensional proteomic, transcriptomic, and epigenetic analyses. T cell assessments identified naive T cells in pre-treatment apheresis associated with good expansion, and exhausted T cells in CAR-T products with poor expansion. Myeloid cell assessment identified CXCR3+ monocytes in pre-treatment apheresis associated with good expansion. Longitudinal analysis of post-treatment samples identified increased CXCR3- classical monocytes in all groups as CAR-T numbers waned. Together, our data uncover mediators of CAR-T biology and correlates of expansion that could be utilized to advance immunotherapies for solid tumor patients.

Immune Profiling Mass Cytometry Assay Harmonization: Multicenter Experience from CIMAC-CIDC.

PURPOSE: The Cancer Immune Monitoring and Analysis Centers - Cancer Immunologic Data Commons (CIMAC-CIDC) Network is supported by the NCI to identify biomarkers of response to cancer immunotherapies across clinical trials using state-of-the-art assays. A primary platform for CIMAC-CIDC studies is cytometry by time of flight (CyTOF), performed at all CIMAC laboratories. To ensure the ability to generate comparable CyTOF data across labs, a multistep cross-site harmonization effort was undertaken. EXPERIMENTAL DESIGN: We first harmonized standard operating procedures (SOPs) across the CIMAC sites. Because of a new acquisition protocol comparing original narrow- or new wide-bore injector introduced by the vendor (Fluidigm), we also tested this protocol across sites before finalizing the harmonized SOP. We then performed cross-site assay harmonization experiments using five shared cryopreserved and one lyophilized internal control peripheral blood mononuclear cell (PBMC) with a shared lyophilized antibody cocktail consisting of 14 isotype-tagged antibodies previously validated, plus additional liquid antibodies. These reagents and samples were distributed to the CIMAC sites and the data were centrally analyzed by manual gating and automated methods (Astrolabe). RESULTS: Average coefficients of variation (CV) across sites for each cell population were reported and compared with a previous multisite CyTOF study. We reached an intersite CV of under 20% for most cell subsets, very similar to a previously published study. CONCLUSIONS: These results establish the ability to reproduce CyTOF data across sites in multicenter clinical trials, and also highlight the importance of quality control procedures, such as the use of spike-in control samples, for tracking variability in this assay.

Network for Biomarker Immunoprofiling for Cancer Immunotherapy: Cancer Immune Monitoring and Analysis Centers and Cancer Immunologic Data Commons (CIMAC-CIDC).

PURPOSE: Immunoprofiling to identify biomarkers and integration with clinical trial outcomes are critical to improving immunotherapy approaches for patients with cancer. However, the translational potential of individual studies is often limited by small sample size of trials and the complexity of immuno-oncology biomarkers. Variability in assay performance further limits comparison and interpretation of data across studies and laboratories. EXPERIMENTAL DESIGN: To enable a systematic approach to biomarker identification and correlation with clinical outcome across trials, the Cancer Immune Monitoring and Analysis Centers and Cancer Immunologic Data Commons (CIMAC-CIDC) Network was established through support of the Cancer MoonshotSM Initiative of the National Cancer Institute (NCI) and the Partnership for Accelerating Cancer Therapies (PACT) with industry partners via the Foundation for the NIH. RESULTS: The CIMAC-CIDC Network is composed of four academic centers with multidisciplinary expertise in cancer immunotherapy that perform validated and harmonized assays for immunoprofiling and conduct correlative analyses. A data coordinating center (CIDC) provides the computational expertise and informatics platforms for the storage, integration, and analysis of biomarker and clinical data. CONCLUSIONS: This overview highlights strategies for assay harmonization to enable cross-trial and cross-site data analysis and describes key elements for establishing a network to enhance immuno-oncology biomarker development. These include an operational infrastructure, validation and harmonization of core immunoprofiling assays, platforms for data ingestion and integration, and access to specimens from clinical trials. Published in the same volume are reports of harmonization for core analyses: whole-exome sequencing, RNA sequencing, cytometry by time of flight, and IHC/immunofluorescence.

Distinct phenotype of CD4+ T cells driving celiac disease identified in multiple autoimmune conditions.

Combining HLA-DQ-gluten tetramers with mass cytometry and RNA sequencing analysis, we find that gluten-specific CD4+ T cells in the blood and intestines of patients with celiac disease display a surprisingly rare phenotype. Cells with this phenotype are also elevated in patients with systemic sclerosis and systemic lupus erythematosus, suggesting a way to characterize CD4+ T cells specific for disease-driving antigens in multiple autoimmune conditions.

Case-control Association Study of Autoimmunity Associated Variants in PDCD1 and Juvenile Idiopathic Arthritis.

PURPOSE: Variants in the gene encoding Programmed Cell Death-1 (PDCD1) have been associated with susceptibility to Systemic Lupus Erythematosus and other autoimmune diseases. Given that clinically distinct autoimmune phenotypes share common genetic susceptibility factors, variants in PDCD-1 were tested for a possible association with Juvenile Idiopathic Arthritis (JIA). METHODS: Four Single Nucleotide Polymorphisms (SNPS) in the PDCD1 gene were genotyped and analyzed: rs7421861, rs11568821, rs10204525, and rs7568402 in 834 cases and 855 controls of Northern European ancestry. Each variant was examined for possible associations with JIA and then analyzed for association with JIA categories. RESULTS: PDCD1 variants showed no association with JIA in the cohort overall (rs7421861 p=0.63, rs11568821 p=0.13, rs10204525 p=0.31, and rs7568402 p=0.45). Stratification by JIA categories indicated a significant association between systemic JIA and PDCD1 rs7568402 (OR=0.53, p=0.0027), which remained significant after 10,000 permutations, but was not replicated in an independent multi-ethnic systemic JIA cohort. A nominal association between enthesitis-related arthritis and rs115668821 was also observed (OR=0.22, p=0.012). CONCLUSION: Unlike other multiple autoimmune disease associated genetic variants, there was no association between PDCD1 variants and JIA or JIA categories.

Limitations in the classification of childhood-onset rheumatoid arthritis.

OBJECTIVE: Rheumatoid factor-positive polyarthritis (RF+ poly) is the juvenile idiopathic arthritis (JIA) category that resembles adult seropositive rheumatoid arthritis (RA). We studied children with RF+ and/or anticyclic citrullinated peptide antibody (anti-CCP)+ JIA to determine what proportion of those children meet International League of Associations for Rheumatology (ILAR) criteria for RF+ poly JIA and to assess for significant differences between children who meet RF+ poly criteria and those who are classified in other categories. METHODS: Charts of children with JIA who were RF+ and/or anti-CCP+ were reviewed. Children with RF+ poly JIA were compared to children in other categories. Statistical analysis was performed using chi-square, Fisher's exact test, and the Student's t-test. RESULTS: Of 56 children with RF+ and/or anti-CCP+ JIA, 34 (61%) met ILAR criteria for RF+ poly JIA. Twelve children had RF-/anti-CCP+ JIA with low anti-CCP titers. When these 12 children were excluded, there were few significant differences between children who met criteria for RF+ poly and those who were classified in other categories. The American College of Rheumatology/European League Against Rheumatism criteria for RA identified more RF+ children than did the ILAR RF+ poly classification (100% vs 77%). CONCLUSION: A number of children with RF+ arthritis were excluded from the RF+ poly JIA classification, though many demographic features and disease measures were similar to those of children who met criteria for RF+ poly JIA. We propose prioritization of RF/anti-CCP positivity over specific exclusions, along with inclusion of anti-CCP, in future revisions of the JIA classification criteria, to improve the sensitivity of diagnosing childhood-onset RA.

Meta-analysis confirms association between TNFA-G238A variant and JIA, and between PTPN22-C1858T variant and oligoarticular, RF-polyarticular and RF-positive polyarticular JIA.

BACKGROUND: Although more than 100 non-HLA variants have been tested for associations with juvenile idiopathic arthritis (JIA) in candidate gene studies, only a few have been replicated. We sought to replicate reported associations of single nucleotide polymorphisms (SNPs) in the PTPN22, TNFA and MIF genes in a well-characterized cohort of children with JIA. METHODS: We genotyped and analyzed 4 SNPs in 3 genes: PTPN22 C1858T (rs2476601), TNFA G-308A, G-238A (rs1800629, rs361525) and MIF G-173C (rs755622) in 647 JIA cases and 751 healthy controls. We tested for association between each variant and JIA as well as JIA subtypes. We adjusted for multiple testing using permutation procedures. We also performed a meta-analysis that combined our results with published results from JIA association studies. RESULTS: While the PTPN22 variant showed only modest association with JIA (OR = 1.29, p = 0.0309), it demonstrated a stronger association with the RF-positive polyarticular JIA subtype (OR = 2.12, p = 0.0041). The MIF variant was not associated with the JIA as a whole or with any subtype. The TNFA-238A variant was associated with JIA as a whole (OR 0.66, p = 0.0265), and demonstrated a stronger association with oligoarticular JIA (OR 0.33, p = 0.0006) that was significant after correction for multiple testing. TNFA-308A was not associated with JIA, but was nominally associated with systemic JIA (OR = 0.33, p = 0.0089) and enthesitis-related JIA (OR = 0.40, p = 0.0144). Meta-analyses confirmed significant associations between JIA and PTPN22 (OR 1.44, p <0.0001) and TNFA-238A (OR 0.69, p < 0.0086) variants. Subtype meta-analyses of the PTPN22 variant revealed associations between RF-positive, RF-negative, and oligoarticular JIA, that remained significant after multiple hypothesis correction (p < 0.0005, p = 0.0007, and p < 0.0005, respectively). CONCLUSIONS: We have confirmed associations between JIA and PTPN22 and TNFA G-308A. By performing subtype analyses, we discovered a statistically-significant association between the TNFA-238A variant and oligoarticular JIA. Our meta-analyses confirm the associations between TNFA-238A and JIA, and show that PTPN22 C1858T is associated with JIA as well as with RF-positive, RF-negative and oligoarticular JIA.