Serum proteomics reveals hemophagocytic lymphohistiocytosis-like phenotype in a subset of patients with multisystem inflammatory syndrome in children.

Children with Multisystem Inflammatory Syndrome in Children (MIS-C) can present with thrombocytopenia, which is a key feature of hemophagocytic lymphohistiocytosis (HLH). We hypothesized that thrombocytopenic MIS-C patients have more features of HLH. Clinical characteristics and routine laboratory parameters were collected from 228 MIS-C patients, of whom 85 (37%) were thrombocytopenic. Thrombocytopenic patients had increased ferritin levels; reduced leukocyte subsets; and elevated levels of ASAT and ALAT. Soluble IL-2RA was higher in thrombocytopenic children than in non-thrombocytopenic children. T-cell activation, TNF-alpha and IFN-gamma signaling markers were inversely correlated with thrombocyte levels, consistent with a more pronounced cytokine storm syndrome. Thrombocytopenia was not associated with severity of MIS-C and no pathogenic variants were identified in HLH-related genes. This suggests that thrombocytopenia in MIS-C is not a feature of a more severe disease phenotype, but the consequence of a distinct hyperinflammatory immunopathological process in a subset of children.

AI-Inclusivity in Healthcare: Motivating an Institutional Epistemic Trust Perspective.

This paper motivates institutional epistemic trust as an important ethical consideration informing the responsible development and implementation of artificial intelligence (AI) technologies (or AI-inclusivity) in healthcare. Drawing on recent literature on epistemic trust and public trust in science, we start by examining the conditions under which we can have institutional epistemic trust in AI-inclusive healthcare systems and their members as providers of medical information and advice. In particular, we discuss that institutional epistemic trust in AI-inclusive healthcare depends, in part, on the reliability of AI-inclusive medical practices and programs, its knowledge and understanding among different stakeholders involved, its effect on epistemic and communicative duties and burdens on medical professionals and, finally, its interaction and alignment with the public's ethical values and interests as well as background sociopolitical conditions against which AI-inclusive healthcare systems are embedded. To assess the applicability of these conditions, we explore a recent proposal for AI-inclusivity within the Dutch Newborn Screening Program. In doing so, we illustrate the importance, scope, and potential challenges of fostering and maintaining institutional epistemic trust in a context where generating, assessing, and providing reliable and timely screening results for genetic risk is of high priority. Finally, to motivate the general relevance of our discussion and case study, we end with suggestions for strategies, interventions, and measures for AI-inclusivity in healthcare more widely.

Systematic reanalysis of genomic data by diagnostic laboratories: a scoping review of ethical, economic, legal and (psycho)social implications.

With the introduction of Next Generation Sequencing (NGS) techniques increasing numbers of disease-associated variants are being identified. This ongoing progress might lead to diagnoses in formerly undiagnosed patients and novel insights in already solved cases. Therefore, many studies suggest introducing systematic reanalysis of NGS data in routine diagnostics. Introduction will, however, also have ethical, economic, legal and (psycho)social (ELSI) implications that Genetic Health Professionals (GHPs) from laboratories should consider before possible implementation of systematic reanalysis. To get a first impression we performed a scoping literature review. Our findings show that for the vast majority of included articles ELSI aspects were not mentioned as such. However, often these issues were raised implicitly. In total, we identified nine ELSI aspects, such as (perceived) professional responsibilities, implications for consent and cost-effectiveness. The identified ELSI aspects brought forward necessary trade-offs for GHPs to consciously take into account when considering responsible implementation of systematic reanalysis of NGS data in routine diagnostics, balancing the various strains on their laboratories and personnel while creating optimal results for new and former patients. Some important aspects are not well explored yet. For example, our study shows GHPs see the values of systematic reanalysis but also experience barriers, often mentioned as being practical or financial only, but in fact also being ethical or psychosocial. Engagement of these GHPs in further research on ELSI aspects is important for sustainable implementation.

Curation and expansion of the Human Phenotype Ontology for systemic autoinflammatory diseases improves phenotype-driven disease-matching.

Introduction: Accurate and standardized phenotypic descriptions are essential in diagnosing rare diseases and discovering new diseases, and the Human Phenotype Ontology (HPO) system was developed to provide a rich collection of hierarchical phenotypic descriptions. However, although the HPO terms for inborn errors of immunity have been improved and curated, it has not been investigated whether this curation improves the diagnosis of systemic autoinflammatory disease (SAID) patients. Here, we aimed to study if improved HPO annotation for SAIDs enhanced SAID identification and to demonstrate the potential of phenotype-driven genome diagnostics using curated HPO terms for SAIDs. Methods: We collected HPO terms from 98 genetically confirmed SAID patients across eight different European SAID expertise centers and used the LIRICAL (Likelihood Ratio Interpretation of Clinical Abnormalities) computational algorithm to estimate the effect of HPO curation on the prioritization of the correct SAID for each patient. Results: Our results show that the percentage of correct diagnoses increased from 66% to 86% and that the number of diagnoses with the highest ranking increased from 38 to 45. In a further pilot study, curation also improved HPO-based whole-exome sequencing (WES) analysis, diagnosing 10/12 patients before and 12/12 after curation. In addition, the average number of candidate diseases that needed to be interpreted decreased from 35 to 2. Discussion: This study demonstrates that curation of HPO terms can increase identification of the correct diagnosis, emphasizing the high potential of HPO-based genome diagnostics for SAIDs.

Clinical Symptoms, Laboratory Parameters and Long-Term Follow-up in a National DADA2 Cohort.

Deficiency of adenosine deaminase-2 (DADA2) is an autosomal recessive autoinflammatory disease with an extremely variable disease presentation. This paper provides a comprehensive overview of the Dutch DADA2 cohort. We performed a retrospective cohort study in 29 ADA2-deficient patients from 23 families with a median age at inclusion of 26 years. All patients had biallelic pathogenic variants in the ADA2 gene. The most common clinical findings included cutaneous involvement (79.3%), (hepato)splenomegaly (70.8%) and recurrent infections (58.6%). Stroke was observed in 41.4% of the patients. The main laboratory abnormalities were hypogammaglobulinemia and various cytopenias. Patients presented most often with a mixed phenotype involving vasculopathy, immunodeficiency and hematologic manifestations (62.1%). In this cohort, malignancies were reported in eight patients (27.6%), of whom five presented with a hematologic malignancy and two with a basal cell carcinoma. Four patients developed hemophagocytic lymphohistiocytosis (HLH) or an HLH-like episode, of whom three passed away during or shortly after the occurrence of HLH. TNF-inhibitors (TNFi) were effective in treating vasculopathy-associated symptoms and preventing stroke, but were hardly effective in the treatment of hematologic manifestations. Three patients underwent hematopoietic cell transplantation and two of them are doing well with complete resolution of DADA2-related symptoms. The overall mortality in this cohort was 17.2%. In conclusion, this cohort describes the clinical, genetic and laboratory findings of 29 Dutch DADA2 patients. We describe the occurrence of HLH as a life-threatening disease complication and report a relatively high incidence of malignancies and mortality.

Dysregulation of miRNA-30e-3p targeting IL-1ß in an international cohort of systemic autoinflammatory disease patients.

Autoinflammation is the standard mechanism seen in systemic autoinflammatory disease (SAID) patients. This study aimed to investigate the effect of a candidate miRNA, miR-30e-3p, which was identified in our previous study, on the autoinflammation phenotype seen in SAID patients and to analyze its expression in a larger group of European SAID patients. We examined the potential anti-inflammatory effect of miR-30e-3p, which we had defined as one of the differentially expressed miRNAs in microarray analysis involved in inflammation-related pathways. This study validated our previous microarray results of miR-30e-3p in a cohort involving European SAID patients. We performed cell culture transfection assays for miR-30e-3p. Then, in transfected cells, we analyzed expression levels of pro-inflammatory genes; IL-1ß, TNF-α, TGF-ß, and MEFV. We also performed functional experiments, caspase-1 activation by fluorometric assay kit, apoptosis assay by flow cytometry, and cell migration assays by wound healing and filter system to understand the possible effect of miR-30e-3p on inflammation. Following these functional assays, 3'UTR luciferase activity assay and western blotting were carried out to identify the target gene of the aforementioned miRNA. MiR-30e-3p was decreased in severe European SAID patients like the Turkish patients. The functional assays associated with inflammation suggested that miR-30e-3p has an anti-inflammatory effect. 3'UTR luciferase activity assay demonstrated that miR-30e-3p directly binds to interleukin-1-beta (IL-1ß), one of the critical molecules of inflammatory pathways, and reduces both RNA and protein levels of IL-1ß. miR-30e-3p, which has been associated with IL-1ß, a principal component of inflammation, might be of potential diagnostic and therapeutic value for SAIDs. KEY MESSAGES: miR-30e-3p, which targets IL-1ß, could have a role in the pathogenesis of SAID patients. miR-30e-3p has a role in regulating inflammatory pathways like migration, caspase-1 activation. miR-30e-3p has the potential to be used for future diagnostic and therapeutic approaches.

Recommendations for whole genome sequencing in diagnostics for rare diseases.

In 2016, guidelines for diagnostic Next Generation Sequencing (NGS) have been published by EuroGentest in order to assist laboratories in the implementation and accreditation of NGS in a diagnostic setting. These guidelines mainly focused on Whole Exome Sequencing (WES) and targeted (gene panels) sequencing detecting small germline variants (Single Nucleotide Variants (SNVs) and insertions/deletions (indels)). Since then, Whole Genome Sequencing (WGS) has been increasingly introduced in the diagnosis of rare diseases as WGS allows the simultaneous detection of SNVs, Structural Variants (SVs) and other types of variants such as repeat expansions. The use of WGS in diagnostics warrants the re-evaluation and update of previously published guidelines. This work was jointly initiated by EuroGentest and the Horizon2020 project Solve-RD. Statements from the 2016 guidelines have been reviewed in the context of WGS and updated where necessary. The aim of these recommendations is primarily to list the points to consider for clinical (laboratory) geneticists, bioinformaticians, and (non-)geneticists, to provide technical advice, aid clinical decision-making and the reporting of the results.

FAIR Genomes metadata schema promoting Next Generation Sequencing data reuse in Dutch healthcare and research.

The genomes of thousands of individuals are profiled within Dutch healthcare and research each year. However, this valuable genomic data, associated clinical data and consent are captured in different ways and stored across many systems and organizations. This makes it difficult to discover rare disease patients, reuse data for personalized medicine and establish research cohorts based on specific parameters. FAIR Genomes aims to enable NGS data reuse by developing metadata standards for the data descriptions needed to FAIRify genomic data while also addressing ELSI issues. We developed a semantic schema of essential data elements harmonized with international FAIR initiatives. The FAIR Genomes schema v1.1 contains 110 elements in 9 modules. It reuses common ontologies such as NCIT, DUO and EDAM, only introducing new terms when necessary. The schema is represented by a YAML file that can be transformed into templates for data entry software (EDC) and programmatic interfaces (JSON, RDF) to ease genomic data sharing in research and healthcare. The schema, documentation and MOLGENIS reference implementation are available at https://fairgenomes.org .

Curation and expansion of Human Phenotype Ontology for defined groups of inborn errors of immunity.

BACKGROUND: Accurate, detailed, and standardized phenotypic descriptions are essential to support diagnostic interpretation of genetic variants and to discover new diseases. The Human Phenotype Ontology (HPO), extensively used in rare disease research, provides a rich collection of vocabulary with standardized phenotypic descriptions in a hierarchical structure. However, to date, the use of HPO has not yet been widely implemented in the field of inborn errors of immunity (IEIs), mainly due to a lack of comprehensive IEI-related terms. OBJECTIVES: We sought to systematically review available terms in HPO for the depiction of IEIs, to expand HPO, yielding more comprehensive sets of terms, and to reannotate IEIs with HPO terms to provide accurate, standardized phenotypic descriptions. METHODS: We initiated a collaboration involving expert clinicians, geneticists, researchers working on IEIs, and bioinformaticians. Multiple branches of the HPO tree were restructured and extended on the basis of expert review. Our ontology-guided machine learning coupled with a 2-tier expert review was applied to reannotate defined subgroups of IEIs. RESULTS: We revised and expanded 4 main branches of the HPO tree. Here, we reannotated 73 diseases from 4 International Union of Immunological Societies-defined IEI disease subgroups with HPO terms. We achieved a 4.7-fold increase in the number of phenotypic terms per disease. Given the new HPO annotations, we demonstrated improved ability to computationally match selected IEI cases to their known diagnosis, and improved phenotype-driven disease classification. CONCLUSIONS: Our targeted expansion and reannotation presents enhanced precision of disease annotation, will enable superior HPO-based IEI characterization, and hence benefit both IEI diagnostic and research activities.

Adult-onset autoinflammation caused by somatic mutations in UBA1: A Dutch case series of patients with VEXAS.

BACKGROUND: A novel autoinflammatory syndrome was recently described in male patients who harbored somatic mutations in the X-chromosomal UBA1 gene. These patients were characterized by adult-onset, treatment-refractory inflammation with fever, cytopenia, dysplastic bone marrow, vacuoles in myeloid and erythroid progenitor cells, cutaneous and pulmonary inflammation, chondritis, and vasculitis, which is abbreviated as VEXAS. OBJECTIVE: This study aimed to (retrospectively) diagnose VEXAS in patients who had previously been registered as having unclassified autoinflammation. We furthermore aimed to describe clinical experiences with this multifaceted, complex disease. METHODS: A systematic reanalysis of whole-exome sequencing data from a cohort of undiagnosed patients with autoinflammation from academic hospitals in The Netherlands was performed. When no sequencing data were available, targeted Sanger sequencing was applied in cases with high clinical suspicion of VEXAS. RESULTS: A total of 12 male patients who carried mutations in UBA1 were identified. These patients presented with adult-onset (mean age 67 years, range 47-79 years) autoinflammation with systemic symptoms, elevated inflammatory parameters, and multiorgan involvement, most typically involving the skin and bone marrow. Novel features of VEXAS included interstitial nephritis, cardiac involvement, stroke, and intestinal perforation related to treatment with tocilizumab. Although many types of treatment were initiated, most patients became treatment-refractory, with a high mortality rate of 50%. CONCLUSION: VEXAS should be considered in the differential diagnosis of males with adult-onset autoinflammation characterized by systemic symptoms and multiorgan involvement. Early diagnosis can prevent unnecessary diagnostic procedures and provide better prognostic information and more suitable treatment options, including stem cell transplantation.

Feasibility of predicting allele specific expression from DNA sequencing using machine learning.

Allele specific expression (ASE) concerns divergent expression quantity of alternative alleles and is measured by RNA sequencing. Multiple studies show that ASE plays a role in hereditary diseases by modulating penetrance or phenotype severity. However, genome diagnostics is based on DNA sequencing and therefore neglects gene expression regulation such as ASE. To take advantage of ASE in absence of RNA sequencing, it must be predicted using only DNA variation. We have constructed ASE models from BIOS (n = 3432) and GTEx (n = 369) that predict ASE using DNA features. These models are highly reproducible and comprise many different feature types, highlighting the complex regulation that underlies ASE. We applied the BIOS-trained model to population variants in three genes in which ASE plays a clinically relevant role: BRCA2, RET and NF1. This resulted in predicted ASE effects for 27 variants, of which 10 were known pathogenic variants. We demonstrated that ASE can be predicted from DNA features using machine learning. Future efforts may improve sensitivity and translate these models into a new type of genome diagnostic tool that prioritizes candidate pathogenic variants or regulators thereof for follow-up validation by RNA sequencing. All used code and machine learning models are available at GitHub and Zenodo.

A Minimal Parameter Set Facilitating Early Decision-making in the Diagnosis of Hemophagocytic Lymphohistiocytosis.

Hemophagocytic lymphohistiocytosis (HLH) is a life-threatening immune dysregulation syndrome characterized by uncontrolled immune cell activation. Timely diagnosis is important, since early treatment can improve survival rates. However, completing all assessments needed to reach ≥5 positive criteria out of the 8 HLH-2004 criteria can be time consuming and may delay timely initiation of treatment. Hence, we applied a data-driven approach to identify a minimal parameter set for early decision-making towards the initiation of HLH-specific treatment. We retrospectively evaluated 165 patients from five Dutch tertiary hospitals with suspected HLH. Sixteen pHLH (median age 0.5 years) and 70 sHLH patients (median age 8.7 years) were identified using the HLH-2004 criteria. Clustering analysis and multi-receiver operator characteristics were used to identify parameters distinctive of HLH. The presence of either increased ferritin, cytopenia in ≥2 lineages, or splenomegaly distinguished HLH from non-HLH cases with a negative predictive value of 100%. A minimal parameter set consisting of 2 major criteria (phagocytosis and splenomegaly) and 3 minor criteria (cytopenia, increased ferritin, and increased triglycerides/low fibrinogen) predicted HLH with 95% (88-99) sensitivity and 94% (86-98) specificity. This finding was replicated in an independent retrospective validation cohort of 109 US patients (n = 109). By dividing a subset of the HLH-2004 criteria into major and minor criteria, this strategy uses the evaluation of less than 5 criteria to quickly identify patients with HLH. When confirmed in a prospective setting, this approach could be of value for timely diagnosis and treatment of HLH.

Implementation of Early Next-Generation Sequencing for Inborn Errors of Immunity: A Prospective Observational Cohort Study of Diagnostic Yield and Clinical Implications in Dutch Genome Diagnostic Centers.

Objective: Inborn errors of immunity (IEI) are a heterogeneous group of disorders, affecting different components of the immune system. Over 450 IEI related genes have been identified, with new genes continually being recognized. This makes the early application of next-generation sequencing (NGS) as a diagnostic method in the evaluation of IEI a promising development. We aimed to provide an overview of the diagnostic yield and time to diagnosis in a cohort of patients suspected of IEI and evaluated by an NGS based IEI panel early in the diagnostic trajectory in a multicenter setting in the Netherlands. Study Design: We performed a prospective observational cohort study. We collected data of 165 patients with a clinical suspicion of IEI without prior NGS based panel evaluation that were referred for early NGS using a uniform IEI gene panel. The diagnostic yield was assessed in terms of definitive genetic diagnoses, inconclusive diagnoses and patients without abnormalities in the IEI gene panel. We also assessed time to diagnosis and clinical implications. Results: For children, the median time from first consultation to diagnosis was 119 days versus 124 days for adult patients (U=2323; p=0.644). The median turn-around time (TAT) of genetic testing was 56 days in pediatric patients and 60 days in adult patients (U=1892; p=0.191). A definitive molecular diagnosis was made in 25/65 (24.6%) of pediatric patients and 9/100 (9%) of adults. Most diagnosed disorders were identified in the categories of immune dysregulation (n=10/25; 40%), antibody deficiencies (n=5/25; 20%), and phagocyte diseases (n=5/25; 20%). Inconclusive outcomes were found in 76/165 (46.1%) patients. Within the patient group with a genetic diagnosis, a change in disease management occurred in 76% of patients. Conclusion: In this cohort, the highest yields of NGS based evaluation for IEI early in the diagnostic trajectory were found in pediatric patients, and in the disease categories immune dysregulation and phagocyte diseases. In cases where a definitive diagnosis was made, this led to important disease management implications in a large majority of patients. More research is needed to establish a uniform diagnostic pathway for cases with inconclusive diagnoses, including variants of unknown significance.

National external quality assessment for next-generation sequencing-based diagnostics of primary immunodeficiencies.

Dutch genome diagnostic centers (GDC) use next-generation sequencing (NGS)-based diagnostic applications for the diagnosis of primary immunodeficiencies (PIDs). The interpretation of genetic variants in many PIDs is complicated because of the phenotypic and genetic heterogeneity. To analyze uniformity of variant filtering, interpretation, and reporting in NGS-based diagnostics for PID, an external quality assessment was performed. Four main Dutch GDCs participated in the quality assessment. Unannotated variant call format (VCF) files of two PID patient analyses per laboratory were distributed among the four GDCs, analyzed, and interpreted (eight analyses in total). Variants that would be reported to the clinician and/or advised for further investigation were compared between the centers. A survey measuring the experiences of clinical laboratory geneticists was part of the study. Analysis of samples with confirmed diagnoses showed that all centers reported at least the variants classified as likely pathogenic (LP) or pathogenic (P) variants in all samples, except for variants in two genes (PSTPIP1 and BTK). The absence of clinical information complicated correct classification of variants. In this external quality assessment, the final interpretation and conclusions of the genetic analyses were uniform among the four participating genetic centers. Clinical and immunological data provided by a medical specialist are required to be able to draw proper conclusions from genetic data.

Parents' Perspectives and Societal Acceptance of Implementation of Newborn Screening for SCID in the Netherlands.

PURPOSE: While neonatal bloodspot screening (NBS) for severe combined immunodeficiency (SCID) has been introduced more than a decade ago, implementation in NBS programs remains challenging in many countries. Even if high-quality test methods and follow-up care are available, public uptake and parental acceptance are not guaranteed. The aim of this study was to describe the parental perspective on NBS for SCID in the context of an implementation pilot. Psychosocial aspects have never been studied before for NBS for SCID and are important for societal acceptance, a major criterion when introducing new disorders in NBS programs. METHODS: To evaluate the perspective of parents, interviews were conducted with parents of newborns with abnormal SCID screening results (N = 17). In addition, questionnaires about NBS for SCID were sent to 2000 parents of healthy newborns who either participated or declined participation in the SONNET-study that screened 140,593 newborns for SCID. RESULTS: Support for NBS for SCID was expressed by the majority of parents in questionnaires from both a public health perspective and a personal perspective. Parents emphasized the emotional impact of an abnormal screening result in interviews. (Long-term) stress and anxiety can be experienced during and after referral indicating the importance of uniform follow-up protocols and adequate information provision. CONCLUSION: The perspective of parents has led to several recommendations for NBS programs that are considering screening for SCID or other disorders. A close partnership of NBS programs' stakeholders, immunologists, geneticists, and pediatricians-immunologists in different countries is required for moving towards universal SCID screening for all infants.

CAPICE: a computational method for Consequence-Agnostic Pathogenicity Interpretation of Clinical Exome variations.

Exome sequencing is now mainstream in clinical practice. However, identification of pathogenic Mendelian variants remains time-consuming, in part, because the limited accuracy of current computational prediction methods requires manual classification by experts. Here we introduce CAPICE, a new machine-learning-based method for prioritizing pathogenic variants, including SNVs and short InDels. CAPICE outperforms the best general (CADD, GAVIN) and consequence-type-specific (REVEL, ClinPred) computational prediction methods, for both rare and ultra-rare variants. CAPICE is easily added to diagnostic pipelines as pre-computed score file or command-line software, or using online MOLGENIS web service with API. Download CAPICE for free and open-source (LGPLv3) at https://github.com/molgenis/capice .