Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Patterns of clinical joint inflammation in juvenile idiopathic arthritis

OBJECTIVES: We studied patterns of joint inflammation in juvenile idiopathic arthritis (JIA) to assess whether joint activity recurs locally in the same joints. METHODS: Joints of 91 patients of the BeSt for Kids study, a treat-to-target trial for children with recent-onset oligoarticular, rheumatoid factor-negative polyarticular and psoriatic JIA, were clinically assessed during 2 years (10 study visits). The association between joint inflammation at baseline and later inflammation in the same joint was assessed using a multilevel mixed-effects logistic regression model at joint level. With a Poisson model, the association between baseline joint inflammation and the number of study visits at which the same joint was recurrently inflamed was tested. RESULTS: Of the 6097 joints studied, 15% (897) was clinically inflamed at baseline. In 42% (377/897) of those joints, inflammation recurred during follow-up. Joint inflammation at baseline was statistically significantly associated with joint inflammation during follow-up in the same joint (OR 3.9, 95% CI 3.5 to 4.4) and specifically with the number of episodes of recurrent joint inflammation (IRR 1.6, 95% CI 1.2 to 2.1). CONCLUSION: In JIA, joint inflammation has the tendency to recur multiple times in joints that are clinically inflamed at disease onset. This indicates that local factors might play a role in the processes contributing to the occurrence of JIA flares

Gene signature fingerprints stratify SLE patients in groups with similar biological disease profiles: a multicentre longitudinal study

OBJECTIVES: Clinical phenotyping and predicting treatment responses in SLE patients is challenging. Extensive blood transcriptional profiling has identified various gene modules that are promising for stratification of SLE patients. We aimed to translate existing transcriptomic data into simpler gene signatures suitable for daily clinical practice. METHODS: Real-time PCR of multiple genes from the IFN M1.2, IFN M5.12, neutrophil (NPh) and plasma cell (PLC) modules, followed by a principle component analysis, was used to identify indicator genes per gene signature. Gene signatures were measured in longitudinal samples from two childhood-onset SLE cohorts (n = 101 and n = 34, respectively), and associations with clinical features were assessed. Disease activity was measured using Safety of Estrogen in Lupus National Assessment (SELENA)-SLEDAI. Cluster analysis subdivided patients into three mutually exclusive fingerprint-groups termed (1) all-signatures-low, (2) only IFN high (M1.2 and/or M5.12) and (3) high NPh and/or PLC. RESULTS: All gene signatures were significantly associated with disease activity in cross-sectionally collected samples. The PLC-signature showed the highest association with disease activity. Interestingly, in longitudinally collected samples, the PLC-signature was associated with disease activity and showed a decrease over time. When patients were divided into fingerprints, the highest disease activity was observed in the high NPh and/or PLC group. The lowest disease activity was observed in the all-signatures-low group. The same distribution was reproduced in samples from an independent SLE cohort. CONCLUSIONS: The identified gene signatures were associated with disease activity and were indicated to be suitable tools for stratifying SLE patients into groups with similar activated immune pathways that may guide future treatment choices

Patterns of clinical joint inflammation in juvenile idiopathic arthritis

Objectives We studied patterns of joint inflammation in juvenile idiopathic arthritis (JIA) to assess whether joint activity recurs locally in the same joints.Methods Joints of 91 patients of the BeSt for Kids study, a treat-to-target trial for children with recent-onset oligoarticular, rheumatoid factor-negative polyarticular and psoriatic JIA, were clinically assessed during 2 years (10 study visits). The association between joint inflammation at baseline and later inflammation in the same joint was assessed using a multilevel mixed-effects logistic regression model at joint level. With a Poisson model, the association between baseline joint inflammation and the number of study visits at which the same joint was recurrently inflamed was tested.Results Of the 6097 joints studied, 15% (897) was clinically inflamed at baseline. In 42% (377/897) of those joints, inflammation recurred during follow-up. Joint inflammation at baseline was statistically significantly associated with joint inflammation during follow-up in the same joint (OR 3.9, 95% CI 3.5 to 4.4) and specifically with the number of episodes of recurrent joint inflammation (IRR 1.6, 95% CI 1.2 to 2.1).Conclusion In JIA, joint inflammation has the tendency to recur multiple times in joints that are clinically inflamed at disease onset. This indicates that local factors might play a role in the processes contributing to the occurrence of JIA flares

Gene signature fingerprints stratify SLE patients in groups with similar biological disease profiles: a multicentre longitudinal study

OBJECTIVES: Clinical phenotyping and predicting treatment responses in SLE patients is challenging. Extensive blood transcriptional profiling has identified various gene modules that are promising for stratification of SLE patients. We aimed to translate existing transcriptomic data into simpler gene signatures suitable for daily clinical practice. METHODS: Real-time PCR of multiple genes from the IFN M1.2, IFN M5.12, neutrophil (NPh) and plasma cell (PLC) modules, followed by a principle component analysis, was used to identify indicator genes per gene signature. Gene signatures were measured in longitudinal samples from two childhood-onset SLE cohorts (n = 101 and n = 34, respectively), and associations with clinical features were assessed. Disease activity was measured using Safety of Estrogen in Lupus National Assessment (SELENA)-SLEDAI. Cluster analysis subdivided patients into three mutually exclusive fingerprint-groups termed (1) all-signatures-low, (2) only IFN high (M1.2 and/or M5.12) and (3) high NPh and/or PLC. RESULTS: All gene signatures were significantly associated with disease activity in cross-sectionally collected samples. The PLC-signature showed the highest association with disease activity. Interestingly, in longitudinally collected samples, the PLC-signature was associated with disease activity and showed a decrease over time. When patients were divided into fingerprints, the highest disease activity was observed in the high NPh and/or PLC group. The lowest disease activity was observed in the all-signatures-low group. The same distribution was reproduced in samples from an independent SLE cohort. CONCLUSIONS: The identified gene signatures were associated with disease activity and were indicated to be suitable tools for stratifying SLE patients into groups with similar activated immune pathways that may guide future treatment choices

Disturbance of Microbial Core Species in New-Onset Juvenile Idiopathic Arthritis

Over the past decades, the intestinal microbiota has increasingly gained attention in studies addressing the pathophysiology of (pediatric) autoimmune diseases, including inflammatory joint diseases, inflammatory bowel disease (IBD), and type 1 diabetes. In this study, we have analyzed the composition of gut microbiota of newly diagnosed juvenile idiopathic arthritis (JIA) patients, prior to initiation of disease-modifying antirheumatic drugs (DMARDs). Fecal microbiota profiles of 8 JIA patients (median age: 11.1 years, 6 girls) were compared with 22 healthy age-matched controls using IS-pro, a 16S-23S interspacer (IS) region-based, eubacterial molecular detection technique. By partial least squares discriminant analysis (PLS-DA), microbiota profiles of JIA and controls could significantly be discriminated based on a limited set of species belonging to the phylum Bacteroidetes ((sic)Fig. 2), but not within other phyla, with a sensitivity of 88%, specificity of 73% ((sic)Fig. 3), and area under the curve (AUC) 0.87 (95% CI: 0.73-0.87). These discriminative species have been considered to be part of the microbial core in healthy children. Conclusion Our findings add to the increasing notion that the gut microbiota may be involved in the pathophysiology of JIA. Species involved in the discrimination between JIA and controls are members of the microbial core in the healthy state. Expanding knowledge on JIA-specificmicrobial signatures and host interactions may open avenues to explore options to develop individualized, microbiota-based preventive, and therapeutic interventions in JI