VarChat: the generative AI assistant for the interpretation of human genomic variations.

MOTIVATION: In the modern era of genomic research, the scientific community is witnessing an explosive growth in the volume of published findings. While this abundance of data offers invaluable insights, it also places a pressing responsibility on genetic professionals and researchers to stay informed about the latest findings and their clinical significance. Genomic variant interpretation is currently facing a challenge in identifying the most up-to-date and relevant scientific papers, while also extracting meaningful information to accelerate the process from clinical assessment to reporting. Computer-aided literature search and summarization can play a pivotal role in this context. By synthesizing complex genomic findings into concise, interpretable summaries, this approach facilitates the translation of extensive genomic datasets into clinically relevant insights. RESULTS: To bridge this gap, we present VarChat (varchat.engenome.com), an innovative tool based on generative AI, developed to find and summarize the fragmented scientific literature associated with genomic variants into brief yet informative texts. VarChat provides users with a concise description of specific genetic variants, detailing their impact on related proteins and possible effects on human health. In addition, VarChat offers direct links to related scientific trustable sources, and encourages deeper research. AVAILABILITY AND IMPLEMENTATION: varchat.engenome.com.

Prevalence and clinical expression of germ line predisposition to myeloid neoplasms in adults with marrow hypocellularity.

Systematic studies of germ line genetic predisposition to myeloid neoplasms in adult patients are still limited. In this work, we performed germ line and somatic targeted sequencing in a cohort of adult patients with hypoplastic bone marrow (BM) to study germ line predisposition variants and their clinical correlates. The study population included 402 consecutive adult patients investigated for unexplained cytopenia and reduced age-adjusted BM cellularity. Germ line mutation analysis was performed using a panel of 60 genes, and variants were interpreted per the American College of Medical Genetics and Genomics/Association for Molecular Pathology guidelines; somatic mutation analysis was performed using a panel of 54 genes. Of the 402 patients, 27 (6.7%) carried germ line variants that caused a predisposition syndrome/disorder. The most frequent disorders were DDX41-associated predisposition, Fanconi anemia, GATA2-deficiency syndrome, severe congenital neutropenia, RASopathy, and Diamond-Blackfan anemia. Eighteen of 27 patients (67%) with causative germ line genotype were diagnosed with myeloid neoplasm, and the remaining with cytopenia of undetermined significance. Patients with a predisposition syndrome/disorder were younger than the remaining patients and had a higher risk of severe or multiple cytopenias and advanced myeloid malignancy. In patients with myeloid neoplasm, causative germ line mutations were associated with increased risk of progression into acute myeloid leukemia. Family or personal history of cancer did not show significant association with a predisposition syndrome/disorder. The findings of this study unveil the spectrum, clinical expressivity, and prevalence of germ line predisposition mutations in an unselected cohort of adult patients with cytopenia and hypoplastic BM.

Critical assessment of variant prioritization methods for rare disease diagnosis within the rare genomes project.

BACKGROUND: A major obstacle faced by families with rare diseases is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years and causal variants are identified in under 50%, even when capturing variants genome-wide. To aid in the interpretation and prioritization of the vast number of variants detected, computational methods are proliferating. Knowing which tools are most effective remains unclear. To evaluate the performance of computational methods, and to encourage innovation in method development, we designed a Critical Assessment of Genome Interpretation (CAGI) community challenge to place variant prioritization models head-to-head in a real-life clinical diagnostic setting. METHODS: We utilized genome sequencing (GS) data from families sequenced in the Rare Genomes Project (RGP), a direct-to-participant research study on the utility of GS for rare disease diagnosis and gene discovery. Challenge predictors were provided with a dataset of variant calls and phenotype terms from 175 RGP individuals (65 families), including 35 solved training set families with causal variants specified, and 30 unlabeled test set families (14 solved, 16 unsolved). We tasked teams to identify causal variants in as many families as possible. Predictors submitted variant predictions with estimated probability of causal relationship (EPCR) values. Model performance was determined by two metrics, a weighted score based on the rank position of causal variants, and the maximum F-measure, based on precision and recall of causal variants across all EPCR values. RESULTS: Sixteen teams submitted predictions from 52 models, some with manual review incorporated. Top performers recalled causal variants in up to 13 of 14 solved families within the top 5 ranked variants. Newly discovered diagnostic variants were returned to two previously unsolved families following confirmatory RNA sequencing, and two novel disease gene candidates were entered into Matchmaker Exchange. In one example, RNA sequencing demonstrated aberrant splicing due to a deep intronic indel in ASNS, identified in trans with a frameshift variant in an unsolved proband with phenotypes consistent with asparagine synthetase deficiency. CONCLUSIONS: Model methodology and performance was highly variable. Models weighing call quality, allele frequency, predicted deleteriousness, segregation, and phenotype were effective in identifying causal variants, and models open to phenotype expansion and non-coding variants were able to capture more difficult diagnoses and discover new diagnoses. Overall, computational models can significantly aid variant prioritization. For use in diagnostics, detailed review and conservative assessment of prioritized variants against established criteria is needed.

Molecular characterization of diffuse large B-cell lymphomas associated with hepatitis C virus infection.

Hepatitis C virus (HCV)-associated diffuse large B-cell lymphoma (DLBCL) displays peculiar clinicopathological characteristics, but its molecular landscape is not fully elucidated. In this study, we investigated the clinicopathological and molecular features of 54 patients with HCV-associated DLBCL. The median age was 71 years. An underlying marginal zone lymphoma component was detected in 14.8% of cases. FISH analysis showed rearrangements involving BCL6 in 50.9% of cases, MYC in 11.3% and BCL2 in 3.7%. Lymph2Cx-based assay was successful in 38 cases, recognizing 16 cases (42.1%) as ABC and 16 cases as GCB subtypes, while six resulted unclassified. ABC cases exhibited a higher lymphoma-related mortality (LRM). Next-generation sequencing analysis showed mutations in 158/184 evaluated genes. The most frequently mutated genes were KMT2D (42.6%), SETD1B (33.3%), RERE (29.4%), FAS and PIM1 (27.8%) and TBL1XR1 (25.9%). A mutation in the NOTCH pathway was detected in 25.9% of cases and was associated with worst LRM. Cluster analysis by LymphGen classified 29/54 cases within definite groups, including BN2 in 14 (48.2%), ST2 in seven (24.2%) and MCD and EZB in four each (13.8%). Overall, these results indicate a preferential marginal zone origin for a consistent subgroup of HCV-associated DLBCL cases and suggest potential implications for molecularly targeted therapies.

Relationship between clone metrics and clinical outcome in clonal cytopenia.

Clonal cytopenia of undetermined significance (CCUS) is associated with an increased risk of developing a myeloid neoplasm with myelodysplasia (MN). To identify the features of the mutant clone(s) that is associated with clinical phenotype and progression, we studied the following cohorts of individuals: 311 patients with idiopathic cytopenia of undetermined significance (ICUS), 532 community-dwelling individuals without hematologic phenotype (n = 355) or with unexplained anemia (n = 177), and 592 patients with overt MN. Ninety-two of 311 (30%) patients with ICUS carried a somatic genetic lesion that signaled CCUS. Clonal hematopoiesis (CH) was detected in 19.7% and 27.7% of nonanemic and anemic community-dwelling individuals, respectively. Different mutation patterns and variant allele frequencies (VAFs) (clone metrics parameters) were observed in the conditions studied. Recurrent mutation patterns exhibited different VAFs associated with marrow dysplasia (0.17-0.48), indicating variable clinical expressivity of mutant clones. Unsupervised clustering analysis based on mutation profiles identified 2 major clusters, characterized by isolated DNMT3A mutations (CH-like cluster) or combinatorial mutation patterns (MN-like cluster), and showing different overall survival (HR, 1.8). In patients with CCUS, the 2 clusters had different risk of progression to MN (HR, 2.7). Within the MN-like cluster, distinct subsets with different risk of progression to MN were identified based on clone metrics. These findings unveil marked variability in the clinical expressivity of myeloid driver genes and underline the limitations of morphologic dysplasia for clinical staging of mutant hematopoietic clones. Clone metrics appears to be critical for informing clinical decision-making in patients with clonal cytopenia.

Incidence and prognosis of clonal hematopoiesis in patients with chronic idiopathic neutropenia.

The incidence and prognosis of clonal hematopoiesis in patients with isolated neutropenia among patients with idiopathic cytopenia of undetermined significance (ICUS), known as ICUS-N or chronic idiopathic neutropenia (CIN) patients, is poorly defined. The current study sought to investigate the frequency and clinical significance of mutations of genes implicated in myeloid malignancies using next-generation sequencing in patients with CIN (n = 185) with a long follow-up. We found that 21 (11.35%) of 185 patients carried a total of 25 somatic mutations in 6 genes with a median variant allele frequency of 12.75%. The most frequently mutated genes were DNMT3A and TET2 involving >80% of patients, followed by IDH1/2, SRSF2, and ZRSR2. The frequency of transformation to a myeloid malignancy was low in the total group of patients (5 of 185 patients [2.70%]). However, from the transformed patients, 4 belonged to the clonal group (4 of 21 [19.05%]) and 1 to the nonclonal group (1 of 164 [0.61%]), indicating that the presence of mutation(s) confers a relative risk for transformation of 31.24 (P = .0017). The variant allele frequency of the mutant clones in the transformed patients was >10% in all cases, and the genes most frequently associated with malignant transformation were SRSF2 and IDH1. No significant differences were identified between the clonal and nonclonal groups in the severity of neutropenia. Patients with clonal disease were older compared with nonclonal patients. These data contribute to the better understanding of the heterogeneous entities underlying ICUS and highlight the importance of mutation analysis for the diagnosis and prognosis of patients with unexplained neutropenias.

Targeted next-generation sequencing reveals molecular heterogeneity in non-chronic lymphocytic leukemia clonal B-cell lymphocytosis.

Non-chronic lymphocytic leukemia (non-CLL) clonal B-cell lymphocytosis (CBL) encompasses a heterogeneous group of hematologic disorders that are still poorly understood. To shed light on their biological aspects, we retrospectively analyzed a highly selected series of 28 patients, who had a clonal B-cell population in the peripheral blood and in the bone marrow, without evidence of lymphoma. Extended targeted next-generation sequencing revealed wide molecular heterogeneity with MYD88 (14%), PDE4DIP (14%), BIRC3 (11%), CCND3 (11%), NOTCH1 (11%), and TNFAIP3 (11%) as the most mutated genes. Mutations of MYD88 were "nonclassic" in most cases. Although some genetic lesions were overlapping with indolent lymphomas, mainly splenic B-cell lymphomas of marginal zone origin and splenic diffuse red pulp small B-cell lymphoma, the genetic profile of our non-CLL CBL series seemed to suggest that various pathways could be involved in the pathogenesis of these disorders, not mirroring any specific lymphoma entity. These data better enlighten the molecular characteristics of non-CLL CBL; however, more efforts are needed in order to improve the diagnostic process, prognostication, and clinical management.

Comprehensive kinome NGS targeted expression profiling by KING-REX.

BACKGROUND: Protein kinases are enzymes controlling different cellular functions. Genetic alterations often result in kinase dysregulation, making kinases a very attractive class of druggable targets in several human diseases. Existing approved drugs still target a very limited portion of the human 'kinome', demanding a broader functional knowledge of individual and co-expressed kinase patterns in physiologic and pathologic settings. The development of novel rapid and cost-effective methods for kinome screening is therefore highly desirable, potentially leading to the identification of novel kinase drug targets. RESULTS: In this work, we describe the development of KING-REX (KINase Gene RNA EXpression), a comprehensive kinome RNA targeted custom assay-based panel designed for Next Generation Sequencing analysis, coupled with a dedicated data analysis pipeline. We have conceived KING-REX for the gene expression analysis of 512 human kinases; for 319 kinases, paired assays and custom analysis pipeline features allow the evaluation of 3'- and 5'-end transcript imbalances as readout for the prediction of gene rearrangements. Validation tests on cell line models harboring known gene fusions demonstrated a comparable accuracy of KING-REX gene expression assessment as in whole transcriptome analyses, together with a robust detection of transcript portion imbalances in rearranged kinases, even in complex RNA mixtures or in degraded RNA. CONCLUSIONS: These results support the use of KING-REX as a rapid and cost effective kinome investigation tool in the field of kinase target identification for applications in cancer biology and other human diseases.

Clinical significance of somatic mutation in unexplained blood cytopenia.

Unexplained blood cytopenias, in particular anemia, are often found in older persons. The relationship between these cytopenias and myeloid neoplasms like myelodysplastic syndromes is currently poorly defined. We studied a prospective cohort of patients with unexplained cytopenia with the aim to estimate the predictive value of somatic mutations for identifying subjects with, or at risk of, developing a myeloid neoplasm. The study included a learning cohort of 683 consecutive patients investigated for unexplained cytopenia, and a validation cohort of 190 patients referred for suspected myeloid neoplasm. Using granulocyte DNA, we looked for somatic mutations in 40 genes that are recurrently mutated in myeloid malignancies. Overall, 435/683 patients carried a somatic mutation in at least 1 of these genes. Carrying a somatic mutation with a variant allele frequency ≥0.10, or carrying 2 or more mutations, had a positive predictive value for diagnosis of myeloid neoplasm equal to 0.86 and 0.88, respectively. Spliceosome gene mutations and comutation patterns involving TET2, DNMT3A, or ASXL1 had positive predictive values for myeloid neoplasm ranging from 0.86 to 1.0. Within subjects with inconclusive diagnostic findings, carrying 1 or more somatic mutations was associated with a high probability of developing a myeloid neoplasm during follow-up (hazard ratio = 13.9, P < .001). The predictive values of mutation analysis were confirmed in the independent validation cohort. The findings of this study indicate that mutation analysis on peripheral blood granulocytes may significantly improve the current diagnostic approach to unexplained cytopenia and more generally the diagnostic accuracy of myeloid neoplasms.

Clinical and molecular characteristics of lymphoplasmacytic lymphoma not associated with an IgM monoclonal protein: A multicentric study of the Rete Ematologica Lombarda (REL) network.

Lymphoplasmacytic lymphoma (LPL) is usually associated with a serum IgM paraprotein, corresponding to Waldenström's Macroglobulinemia (WM). Cases presenting with IgG or IgA, or without a monoclonal protein are extremely rare. We analyzed clinical characteristics, frontline treatment, and the outcome of 45 patients with non-IgM LPL, and compared them with a control group of WM patients. The median age was similar, with significantly higher prevalence of females in non-IgM LPL, than in WM patients (60% vs 39%, P = .016). Patients with non-IgM LPL more frequently presented with lymphadenopathies (53% vs 15%, P < .001), splenomegaly (22% vs 8%, P = .015) or extranodal involvement (20% vs 8%, P = .05). In non-IgM LPL a serum monoclonal protein and bone marrow infiltration were less common than in WM patients (69% and 84% of cases respectively, P < .001 for both comparisons). The MYD88 (L265P) mutation was found in 8/19 patients using allele-specific polymerase chain reaction. A CXCR4 mutation was found in 4/17 cases using Sanger. In 16 patients we performed targeted next-generation sequencing of genes MYD88, CXCR4, ARID1-A, KMT2D, NOTCH2, TP53, PRDM1, CD79B, TRAF3, MYBBP1A, TNFAIP3. Seven patients (44%) had a MYD88 mutation (S219C in one), four (25%) a CXCR4 mutation, three (19%) a KMT2D mutation, one (6%) a TP53 mutation and one (6%) a TRAF3 mutation. With a median follow-up of 55.7 months, 36 non-IgM LPL patients (80%) were treated. Non-IgM LPL patients received more frequently anthracycline-containing regimens, as compared with WM patients, who mainly received alkylating-based therapies. Five-year overall survival (OS) was 84%, similar to that of WM patients.

Integrating clinical features and genetic lesions in the risk assessment of patients with chronic myelomonocytic leukemia.

Chronic myelomonocytic leukemia (CMML) is a myelodysplastic/myeloproliferative neoplasm with variable clinical course. To predict the clinical outcome, we previously developed a CMML-specific prognostic scoring system (CPSS) based on clinical parameters and cytogenetics. In this work, we tested the hypothesis that accounting for gene mutations would further improve risk stratification of CMML patients. We therefore sequenced 38 genes to explore the role of somatic mutations in disease phenotype and clinical outcome. Overall, 199 of 214 (93%) CMML patients carried at least 1 somatic mutation. Stepwise linear regression models showed that these mutations accounted for 15% to 24% of variability of clinical phenotype. Based on multivariable Cox regression analyses, cytogenetic abnormalities and mutations in RUNX1, NRAS, SETBP1, and ASXL1 were independently associated with overall survival (OS). Using these parameters, we defined a genetic score that identified 4 categories with significantly different OS and cumulative incidence of leukemic evolution. In multivariable analyses, genetic score, red blood cell transfusion dependency, white blood cell count, and marrow blasts retained independent prognostic value. These parameters were included into a clinical/molecular CPSS (CPSS-Mol) model that identified 4 risk groups with markedly different median OS (from >144 to 18 months, hazard ratio [HR] = 2.69) and cumulative incidence of leukemic evolution (from 0% to 48% at 4 years, HR = 3.84) (P < .001). The CPSS-Mol fully retained its ability to risk stratify in an independent validation cohort of 260 CMML patients. In conclusion, integrating conventional parameters and gene mutations significantly improves risk stratification of CMML patients, providing a robust basis for clinical decision-making and a reliable tool for clinical trials.

Comparative genomics shows that viral integrations are abundant and express piRNAs in the arboviral vectors Aedes aegypti and Aedes albopictus.

BACKGROUND: Arthropod-borne viruses (arboviruses) transmitted by mosquito vectors cause many important emerging or resurging infectious diseases in humans including dengue, chikungunya and Zika. Understanding the co-evolutionary processes among viruses and vectors is essential for the development of novel transmission-blocking strategies. Episomal viral DNA fragments are produced from arboviral RNA upon infection of mosquito cells and adults. Additionally, sequences from insect-specific viruses and arboviruses have been found integrated into mosquito genomes. RESULTS: We used a bioinformatic approach to analyse the presence, abundance, distribution, and transcriptional activity of integrations from 425 non-retroviral viruses, including 133 arboviruses, across the presently available 22 mosquito genome sequences. Large differences in abundance and types of viral integrations were observed in mosquito species from the same region. Viral integrations are unexpectedly abundant in the arboviral vector species Aedes aegypti and Ae. albopictus, in which they are approximately ~10-fold more abundant than in other mosquito species analysed. Additionally, viral integrations are enriched in piRNA clusters of both the Ae. aegypti and Ae. albopictus genomes and, accordingly, they express piRNAs, but not siRNAs. CONCLUSIONS: Differences in the number of viral integrations in the genomes of mosquito species from the same geographic area support the conclusion that integrations of viral sequences is not dependent on viral exposure, but that lineage-specific interactions exist. Viral integrations are abundant in Ae. aegypti and Ae. albopictus, and represent a thus far underappreciated component of their genomes. Additionally, the genome locations of viral integrations and their production of piRNAs indicate a functional link between viral integrations and the piRNA pathway. These results greatly expand the breadth and complexity of small RNA-mediated regulation and suggest a role for viral integrations in antiviral defense in these two mosquito species.

Pattern of somatic mutations in patients with Waldenström macroglobulinemia or IgM monoclonal gammopathy of undetermined significance.

We analyzed MYD88 and CXCR4 mutation status of 260 patients with Waldenström macroglobulinemia or IgM monoclonal gammopathy of undetermined significance using allele-specific real time quantitative polymerase chain reaction and Sanger sequencing, respectively. A subgroup of 119 patients was further studied with next-generation sequencing of 11 target genes (MYD88, CXCR4, ARID1A, KMT2D, NOTCH2, TP53, PRDM1, CD79B, TRAF3, MYBBP1A, and TNFAIP3). MYD88 (L265P) was found at diagnosis in 91% of patients with Waldenström macroglobulinemia and in 60% of patients with IgM monoclonal gammopathy of undetermined significance using allele-specific polymerase chain reaction analysis. MYD88 mutations other than the classical L265P (V217F, S219C and M232T) were found in four cases by next-generation sequencing. Waldenström macroglobulinemia patients with wild-type MYD88 had a distinct clinical phenotype characterized by less bone marrow infiltration (P=0.01) and more frequent extramedullary involvement (P=0.001) compared to patients with mutated MYD88 Patients with wild-type MYD88 did not show additional mutations in the other target genes. CXCR4 mutations were found by Sanger sequencing in 22% of patients with Waldenström macroglobulinemia. With next-generation sequencing, a CXCR4 mutation was detected in 23% of patients with Waldenström macroglobulinemia and 9% of those with IgM monoclonal gammopathy of undetermined significance. Asymptomatic Waldenström macroglobulinemia patients harboring a CXCR4 mutation had a shorter treatment-free survival (51 months) than that of patients with wild-type CXCR4 (median not reached) (P=0.007). Analysis of variant allele frequencies indicated that CXCR4 mutations were present in the dominant clone in the majority of cases. Recurrent somatic mutations of KMT2D were found in 24% of patients with Waldenström macroglobulinemia and 5% of patients with IgM monoclonal gammopathy of undetermined significance and were primarily subclonal.

BigQ: a NoSQL based framework to handle genomic variants in i2b2.

BACKGROUND: Precision medicine requires the tight integration of clinical and molecular data. To this end, it is mandatory to define proper technological solutions able to manage the overwhelming amount of high throughput genomic data needed to test associations between genomic signatures and human phenotypes. The i2b2 Center (Informatics for Integrating Biology and the Bedside) has developed a widely internationally adopted framework to use existing clinical data for discovery research that can help the definition of precision medicine interventions when coupled with genetic data. i2b2 can be significantly advanced by designing efficient management solutions of Next Generation Sequencing data. RESULTS: We developed BigQ, an extension of the i2b2 framework, which integrates patient clinical phenotypes with genomic variant profiles generated by Next Generation Sequencing. A visual programming i2b2 plugin allows retrieving variants belonging to the patients in a cohort by applying filters on genomic variant annotations. We report an evaluation of the query performance of our system on more than 11 million variants, showing that the implemented solution scales linearly in terms of query time and disk space with the number of variants. CONCLUSIONS: In this paper we describe a new i2b2 web service composed of an efficient and scalable document-based database that manages annotations of genomic variants and of a visual programming plug-in designed to dynamically perform queries on clinical and genetic data. The system therefore allows managing the fast growing volume of genomic variants and can be used to integrate heterogeneous genomic annotations.

A kinetic model-based algorithm to classify NGS short reads by their allele origin.

Genotyping Next Generation Sequencing (NGS) data of a diploid genome aims to assign the zygosity of identified variants through comparison with a reference genome. Current methods typically employ probabilistic models that rely on the pileup of bases at each locus and on a priori knowledge. We present a new algorithm, called Kimimila (KInetic Modeling based on InforMation theory to Infer Labels of Alleles), which is able to assign reads to alleles by using a distance geometry approach and to infer the variant genotypes accurately, without any kind of assumption. The performance of the model has been assessed on simulated and real data of the 1000 Genomes Project and the results have been compared with several commonly used genotyping methods, i.e., GATK, Samtools, VarScan, FreeBayes and Atlas2. Despite our algorithm does not make use of a priori knowledge, the percentage of correctly genotyped variants is comparable to these algorithms. Furthermore, our method allows the user to split the reads pool depending on the inferred allele origin.

Critical assessment of variant prioritization methods for rare disease diagnosis within the Rare Genomes Project.

Background: A major obstacle faced by rare disease families is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years, and causal variants are identified in under 50%. The Rare Genomes Project (RGP) is a direct-to-participant research study on the utility of genome sequencing (GS) for diagnosis and gene discovery. Families are consented for sharing of sequence and phenotype data with researchers, allowing development of a Critical Assessment of Genome Interpretation (CAGI) community challenge, placing variant prioritization models head-to-head in a real-life clinical diagnostic setting. Methods: Predictors were provided a dataset of phenotype terms and variant calls from GS of 175 RGP individuals (65 families), including 35 solved training set families, with causal variants specified, and 30 test set families (14 solved, 16 unsolved). The challenge tasked teams with identifying the causal variants in as many test set families as possible. Ranked variant predictions were submitted with estimated probability of causal relationship (EPCR) values. Model performance was determined by two metrics, a weighted score based on rank position of true positive causal variants and maximum F-measure, based on precision and recall of causal variants across EPCR thresholds. Results: Sixteen teams submitted predictions from 52 models, some with manual review incorporated. Top performing teams recalled the causal variants in up to 13 of 14 solved families by prioritizing high quality variant calls that were rare, predicted deleterious, segregating correctly, and consistent with reported phenotype. In unsolved families, newly discovered diagnostic variants were returned to two families following confirmatory RNA sequencing, and two prioritized novel disease gene candidates were entered into Matchmaker Exchange. In one example, RNA sequencing demonstrated aberrant splicing due to a deep intronic indel in ASNS, identified in trans with a frameshift variant, in an unsolved proband with phenotype overlap with asparagine synthetase deficiency. Conclusions: By objective assessment of variant predictions, we provide insights into current state-of-the-art algorithms and platforms for genome sequencing analysis for rare disease diagnosis and explore areas for future optimization. Identification of diagnostic variants in unsolved families promotes synergy between researchers with clinical and computational expertise as a means of advancing the field of clinical genome interpretation.

Enrichment of Double RUNX1 Mutations in Acute Leukemias of Ambiguous Lineage.

Acute leukemia of ambiguous lineage (ALAL) is a rare type of leukemia and represents an unmet clinical need. In fact, due to heterogeneity, substantial rarity and absence of clinical trials, there are no therapeutic guidelines available. We investigated the genetic basis of 10 cases of ALAL diagnosed at our centre from 2008 and 2020, through a targeted myeloid and lymphoid sequencing approach. We show that this rare group of acute leukemias is enriched in myeloid-gene mutations. In particular we found that RUNX1 mutations, which have been found double mutated in 40% of patients and tend to involve both alleles, are associated with an undifferentiated phenotype and with lineage ambiguity. Furthermore, because this feature is typical of acute myeloid leukemia with minimal differentiation, we believe that our data strengthen the idea that acute leukemia with ambiguous lineage, especially those with an undifferentiated phenotype, might be genetically more closer to acute myeloid leukemia rather than acute lymphoblastic leukemia. These data enrich the knowledge on the genetic basis of ALAL and could have clinical implications as an acute myeloid leukemia (AML) - oriented chemotherapeutic approach might be more appropriate.