ObjectiveTo investigate the characteristics and risk factors of a novel parenchymal lung disease (LD), increasingly detected in systemic juvenile idiopathic arthritis (sJIA).MethodsIn a multicentre retrospective study, 61 cases were investigated using physician-reported clinical information and centralised analyses of radiological, pathological and genetic data.ResultsLD was associated with distinctive features, including acute erythematous clubbing and a high frequency of anaphylactic reactions to the interleukin (IL)-6 inhibitor, tocilizumab. Serum ferritin elevation and/or significant lymphopaenia preceded LD detection. The most prevalent chest CT pattern was septal thickening, involving the periphery of multiple lobes ± ground-glass opacities. The predominant pathology (23 of 36) was pulmonary alveolar proteinosis and/or endogenous lipoid pneumonia (PAP/ELP), with atypical features including regional involvement and concomitant vascular changes. Apparent severe delayed drug hypersensitivity occurred in some cases. The 5-year survival was 42%. Whole exome sequencing (20 of 61) did not identify a novel monogenic defect or likely causal PAP-related or macrophage activation syndrome (MAS)-related mutations. Trisomy 21 and young sJIA onset increased LD risk. Exposure to IL-1 and IL-6 inhibitors (46 of 61) was associated with multiple LD features. By several indicators, severity of sJIA was comparable in drug-exposed subjects and published sJIA cohorts. MAS at sJIA onset was increased in the drug-exposed, but was not associated with LD features.ConclusionsA rare, life-threatening lung disease in sJIA is defined by a constellation of unusual clinical characteristics. The pathology, a PAP/ELP variant, suggests macrophage dysfunction. Inhibitor exposure may promote LD, independent of sJIA severity, in a small subset of treated patients. Treatment/prevention strategies are needed.

Patient genomes are interpretable only in the context of other genomes; however, genome sharing enables discrimination. Thousands of monogenic diseases have yielded definitive genomic diagnoses and potential gene therapy targets. Here we show how to provide such diagnoses while preserving participant privacy through the use of secure multiparty computation. In multiple real scenarios (small patient cohorts, trio analysis, two-hospital collaboration), we used our methods to identify the causal variant and discover previously unrecognized disease genes and variants while keeping up to 99.7% of all participants' most sensitive genomic information private.

The diagnosis of Mendelian disorders requires labor-intensive literature research. Trained clinicians can spend hours looking for the right publication(s) supporting a single gene that best explains a patient’s disease. AMELIE (Automatic Mendelian Literature Evaluation) greatly accelerates this process. AMELIE parses all 29 million PubMed abstracts and downloads and further parses hundreds of thousands of full-text articles in search of information supporting the causality and associated phenotypes of most published genetic variants. AMELIE then prioritizes patient candidate variants for their likelihood of explaining any patient’s given set of phenotypes. Diagnosis of singleton patients (without relatives’ exomes) is the most time-consuming scenario, and AMELIE ranked the causative gene at the very top for 66% of 215 diagnosed singleton Mendelian patients from the Deciphering Developmental Disorders project. Evaluating only the top 11 AMELIE-scored genes of 127 (median) candidate genes per patient resulted in a rapid diagnosis in more than 90% of cases. AMELIE-based evaluation of all cases was 3 to 19 times more efficient than hand-curated database–based approaches. We replicated these results on a retrospective cohort of clinical cases from Stanford Children’s Health and the Manton Center for Orphan Disease Research. An analysis web portal with our most recent update, programmatic interface, and code is available at AMELIE.stanford.edu.

Objective To investigate characteristics and risk factors of a novel parenchymal lung disease, increasingly detected in systemic juvenile idiopathic arthritis (sJIA). Methods In a multi-center retrospective study, 61 cases were investigated, using physician-reported clinical information and centralized analyses of radiologic, pathologic and genetic data. Results Lung disease (LD) was associated with distinctive features, including acute erythematous clubbing and a high frequency of anaphylactic reactions to the IL-6 inhibitor, tocilizumab. Serum ferritin elevation and/or significant lymphopenia preceded LD detection. The most prevalent chest CT pattern was septal thickening, involving the periphery of multiple lobes +/- ground glass opacities. Predominant pathology (23/36) was pulmonary alveolar proteinosis and/or endogenous lipoid pneumonia (PAP/ELP), with atypical features, including regional involvement and concomitant vascular changes. Apparent severe delayed drug hypersensitivity occurred in some cases. 5-year survival was 42%. Whole-exome sequencing (20/61) did not identify a novel monogenic defect PAP-related or macrophage activation syndrome (MAS)-related mutations as likely primary cause. Trisomy 21 (T21) increased LD risk, as did young sJIA onset. Refractory sJIA was not required for LD development. Exposure to interleukin (IL)-1 and IL-6 inhibitors (46/61) was associated with multiple LD features. By several indicators, severity of sJIA was comparable in drug-exposed subjects and published sJIA cohorts. MAS at sJIA onset was increased in the drug-exposed, but it was not associated with LD features. Conclusions A rare, life-threatening LD in sJIA is defined by a constellation of unusual clinical characteristics. The pathology, a PAP/ELP variant, suggests macrophage dysfunction. Inhibitor exposure may promote LD, independent of sJIA severity, in a small subset of treated patients. Treatment/prevention strategies are needed.

Purpose: Diagnosing monogenic diseases facilitates optimal care, but can involve the manual evaluation of hundreds of genetic variants per case. Computational tools like Phrank expedite this process by ranking all candidate genes by their ability to explain the patient’s phenotypes. To use these tools, busy clinicians must manually encode patient phenotypes from lengthy clinical notes. With 100 million human genomes estimated to be sequenced by 2025, a fast alternative to manual phenotype extraction from clinical notes will become necessary. Methods: We introduce ClinPhen, a fast, high-accuracy tool that automatically converts clinical notes into a prioritized list of patient phenotypes using Human Phenotype Ontology (HPO) terms. Results: ClinPhen shows superior accuracy and 20× speedup over existing phenotype extractors, and its novel phenotype prioritization scheme improves the performance of gene-ranking tools. Conclusion: While a dedicated clinician can process 200 patient records in a 40-hour workweek, ClinPhen does the same in 10 minutes. Compared with manual phenotype extraction, ClinPhen saves an additional 3–5 hours per Mendelian disease diagnosis. Providers can now add ClinPhen’s output to each summary note attached to a filled testing laboratory request form. ClinPhen makes a substantial contribution to improvements in efficiency critically needed to meet the surging demand for clinical diagnostic sequencing.