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

Modeling Relational Data with Graph Convolutional Networks

Knowledge graphs enable a wide variety of applications, including question answering and information retrieval. Despite the great effort invested in their creation and maintenance, even the largest (e.g., Yago, DBPedia or Wikidata) remain incomplete. We introduce Relational Graph Convolutional Networks (R-GCNs) and apply them to two standard knowledge base completion tasks: Link prediction (recovery of missing facts, i.e. subject-predicate-object triples) and entity classification (recovery of missing entity attributes). R-GCNs are related to a recent class of neural networks operating on graphs, and are developed specifically to deal with the highly multi-relational data characteristic of realistic knowledge bases. We demonstrate the effectiveness of R-GCNs as a stand-alone model for entity classification. We further show that factorization models for link prediction such as DistMult can be significantly improved by enriching them with an encoder model to accumulate evidence over multiple inference steps in the relational graph, demonstrating a large improvement of 29.8% on FB15k-237 over a decoder-only baseline

Two novel cases expanding the phenotype of SETD2-related overgrowth syndrome

The SETD2-related overgrowth syndrome is also called "Luscan-Lumish syndrome" (OMIM 616831) with the clinical characteristics of intellectual disability, speech delay, macrocephaly, facial dysmorphism, and autism spectrum disorders. We report on two novel patients a 4.5-year-old boy and a 23-year-old female adolescent with a speech and language developmental delay, autism spectrum disorder and macrocephaly, who were both diagnosed with SETD2-related overgrowth syndrome due to de novo frameshift mutations in the SETD2 gene. Features not previously described which were present in either one of our patients were nasal polyps, a large tongue with creases, a high pain threshold, constipation, and undescended testicles. These features may be related to the syndrome and may need special attention in future patients. Additionally, prevention of obesity should be an important point of attention for patients diagnosed with a SETD2-related overgrowth syndrome

High-frequency type I/II mutational shifts between diagnosis and relapse are associated with outcome in pediatric AML: Implications for personalized medicine

Although virtually all pediatric patients with acute myeloid leukemia (AML) achieve a complete remission after initial induction therapy, 30%-40% of patients will encounter a relapse and have a dismal prognosis. To prevent relapses, personalized treatment strategies are currently being developed, which target specific molecular aberrations. To determine relevance of established AML type I/II mutations that may serve as therapeutic targets, we assessed frequencies of these mutations and their persistence during disease progression in a large group (n = 69) of paired diagnosis and relapse pediatric AML specimens. In 26 of 42 patients (61%) harboring mutations at either stage of the disease, mutation status changed between diagnosis and relapse, particularly in FLT3, WT1, and RAS genes. Presence or gain of type I/II mutations at relapse was associated with a shorter time to relapse (TTR), whereas absence or loss correlated with longer TTR. Moreover, an adverse outcome was found for patients with activating mutations at relapse, which was statistically significant for FLT3/ITD and WT1 mutations. These findings suggest that mutational shifts affect disease progression. We hence propose that risk stratification, malignant cell detection, and selection of personalized treatment should be based on status of type I/II mutations both at initial diagnosis and during follow-up

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

Item does not contain fulltextDutch 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

Standardization of WT1 mRNA quantitation for minimal residual disease monitoring in childhood AML and implications of WT1 gene mutations: a European multicenter study

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