Era Of Next-generation Sequencing Research Articles

The Role of ctDNA in the Management of Non-Small-Cell Lung Cancer in the AI and NGS Era.

Liquid biopsy (LB) involves the analysis of circulating tumour-derived DNA (ctDNA), providing a minimally invasive method for gathering both quantitative and qualitative information. Genomic analysis of ctDNA through next-generation sequencing (NGS) enables comprehensive genetic profiling of tumours, including non-driver alterations that offer prognostic insights. LB can be applied in both early-stage disease settings, for the diagnosis and monitoring of minimal residual disease (MRD), and advanced disease settings, for monitoring treatment response and understanding the mechanisms behind disease progression and tumour heterogeneity. Currently, LB has limited use in clinical practice, primarily due to its significant costs, limited diagnostic yield, and uncertain prognostic role. The application of artificial intelligence (AI) in the medical field is a promising approach to processing extensive information and applying it to individual cases to enhance therapeutic decision-making and refine risk assessment.

Acute myeloid leukemia in the next-generation sequencing era : Real-world data from an Austrian tertiary cancer care center.

Next-generation sequencing (NGS) has recently entered routine acute myeloid leukemia (AML) diagnostics. It is paramount for AML risk stratification and identification of molecular therapeutic targets. Most NGS feasibility and results data are derived from controlled clinical intervention trials (CCIT). We aimed to validate these data in areal-world setting. This study retrospectively analyzed 447 AML patients treated at an Austrian tertiary cancer care center. A total of 284 out of the 447 cases were treated between 2013-2023 when NGS was locally available for the clinical routine. The NGS was successfully performed from bone marrow biopsies and aspirates, with processing times decreasing from 22days in 2013/2014 to 10days in 2022. Molecular therapeutic target(s) were identified by NGS in 107/284 (38%) cases and enabled risk stratification in 10 cases where conventional karyotyping failed. Concerning molecular landscape, TET2 (27%), FLT3 (25%), DNMT3A (23%), and NPM1 (23%) were most frequently mutated. Comparing older and younger patients (cut-off 70years) showed enrichment in older people for mutations affecting DNA methylation (72% vs.45%; P < 0.001) and the spliceosome (28% vs. 11%; P = 0.006) and more cellular signaling mutations in younger patients (61% vs. 46%; P = 0.022). Treatment outcomes corroborated asignificant survival benefit in the recent NGS era and patients treated with novel/molecularly targeted drugs. Ultimately, biospecimens of these patients are stored within aleukemia biobank, generating avaluable tool for translational science. Our study validates data from CCIT and supports their relevance for treatment decisions in areal-world setting. Moreover, they demonstrate the feasibility and benefits of NGS within aroutine clinical setting.

Therapeutic implications of etiology-specific diagnosis of early-onset developmental and epileptic encephalopathies (EO-DEEs): A nationwide Turkish cohort study

ObjectiveTo evaluate the etiology-specific diagnosis of early-onset developmental epileptic encephalopathies (EO-DEEs) in a nationwide Turkish cohort to determine the implications for therapeutic management. MethodsThe cohort comprised 1450 patients who underwent EO-DEE. The utility of genetic testing was assessed with respect to the initial phases of next generation sequencing (NGS) (2005–2013) and the current NGS era (2014–2022). A predefined four-stepwise diagnostic model was evaluated using cost-effectiveness analysis. The diagnostic and potential therapeutic yields of the genetic tests were subsequently determined. ResultsGene-related EO-DEEs were identified in 48.3 % (n = 701) of the cohort: non-structural genetic (62.6 %), metabolic genetic (15.1 %), and structural genetic (14.1 %). The most common nonstructural genetic variants were SCN1A (n = 132, 18.8 %), CDKL5 (n = 30, 4.2 %), STXBP1 (n = 21, 2.9 %), KCNQ2 (n = 21, 2.9 %), and PCDH19 (n = 17, 2.4 %). The rate of ultra-rare variants (< 0.5 %) was higher in the NGS era (52 %) than that in the initial phase (36 %). The potential therapeutic yields with precision therapy and antiseizure drug modification were defined in 34.5 % and 56.2 % in genetic-EO-DEEs, respectively. The diagnostic model provided an etiology-specific diagnosis at a rate of 78.7 %: structural (nongenetic) (31.4 %), genetic (38.5 %), metabolic (6.1 %), and immune-infectious (2.8 %). Based on a cost-effectiveness analysis, the presented diagnostic model indicated the early implementation of whole-exome sequencing for EO-DEEs. SignificanceIn the present cohort, the higher rate (48.3 %) of gene-related EO-DEE diagnoses in the NGS era provides a potential therapeutic management plan for more patients.

Prenatal Diagnosed Agenesis of the Corpus Callosum: Identifying the Underlying Genetic Etiologies.

To assess the genetic etiologies underlying agenesis of the corpus callosum (ACC) and its pregnancy outcomes in the era of next-generation sequencing. A retrospective analysis was conducted on prospectively collected prenatal ACC cases in which amniocentesis was performed between January 2016 and December 2022. ACC was divided into non-isolated and isolated according to the presence or absence of ultrasound abnormalities. Chromosomal microarray analysis (CMA), karyotyping and exome sequencing (ES) were performed after genetic counseling. Pregnancy outcomes were assessed by pediatric neurosurgeons and were followed up by telephone through their parents. Sixty-eight fetuses with ACC were enrolled in this study. CMA detected eight cases with pathogenic copy number variants (CNVs) and all were non-isolated ACC, with a detection rate of 11.8% (8/68). Among the CMA abnormalities, the majority (6/8) were detectable by karyotyping. ES was performed in 26 cases with normal CMA, revealing pathogenic or likely pathogenic gene variations in 12 cases (46.2%, 12/26), involving L1CMA, SMARCB1, PPP2R1A, ARID1B, USP34, CDC42, NFIA and DCC genes. The detection rates of ES in isolated and non-isolated ACC were 40% (6/15) and 54.5% (6/11), respectively. After excluding cases where pregnancy was terminated (56 cases), there were 12 live births, ranging in age from 15months to 7years. Of these, 91.7% (11 out of 12) demonstrated normal neurodevelopmental outcomes. Specifically, all five cases with isolated ACC and negative ES results exhibited normal neurodevelopment. The remaining six cases with favorable outcomes were all isolated ACC, among which ES identified variants of DCC and USP34 gene in one each case. The other four cases were CMA-negative and declined ES. We highlight the efficacy of prenatal ES in determining the genetic etiology of ACC, whether isolated or not. Favorable neurodevelopmental outcomes were observed when ACC was isolated and with normal ES results.

Assessing the Relevance of Non-molecular Prognostic Systems for Myelodysplastic Syndrome in the Era of Next-Generation Sequencing.

The Molecular International Prognostic Scoring System (IPSS-M) has improved the prediction of clinical outcomes for myelodysplastic syndromes (MDS). The Artificial Intelligence Prognostic Scoring System for MDS (AIPSS-MDS), based on classical clinical parameters, has outperformed the IPSS, revised version (IPSS-R). For the first time, we validated the IPSS-M and other molecular prognostic models and compared them with the established IPSS-R and AIPSS-MDS models using data from South American patients. Molecular and clinical data from 145 patients with MDS and 37 patients with MDS/myeloproliferative neoplasms were retrospectively analyzed. Prognostic power evaluation revealed that the IPSS-M (Harrell's concordance [C]-index: 0.75, area under the receiver operating characteristic curve [AUC]: 0.68) predicted overall survival better than the European MDS (EuroMDS; C-index: 0.72, AUC: 0.68) and Munich Leukemia Laboratory (MLL) (C-index: 0.70, AUC: 0.64) models. The IPSS-M prognostic discrimination was similar to that of the AIPSS-MDS model (C-index: 0.74, AUC: 0.66) and outperformed the IPSS-R model (C-index: 0.70, AUC: 0.61). Considering simplified low- and high-risk groups for clinical management, after restratifying from IPSS-R (57% and 32%, respectively, hazard ratio [HR]: 2.8; P=0.002) to IPSS-M, 12.6% of patients were upstaged, and 5% were downstaged (HR: 2.9; P=0.001). The AIPSS-MDS recategorized 51% of the low-risk cohort as high-risk, with no patients being downstaged (HR: 5.6; P<0.001), consistent with most patients requiring disease-modifying therapy. The IPSS-M and AIPSS-MDS models provide more accurate survival prognoses than the IPSS-R, EuroMDS, and MLL models. The AIPSS-MDS model is a valid option for assessing risks for all patients with MDS, especially in resource-limited centers where molecular testing is not currently a standard clinical practice.

Short Tandem Repeats in the era of next-generation sequencing: from historical loci to population databases.

In this study, we explore the landscape of short tandem repeats (STRs) within the human genome through the lens of evolving technologies to detect genomic variations. STRs, which encompass approximately 3% of our genomic DNA, are crucial for understanding human genetic diversity, disease mechanisms, and evolutionary biology. The advent of high-throughput sequencing methods has revolutionized our ability to accurately map and analyze STRs, highlighting their significance in genetic disorders, forensic science, and population genetics. We review the current available methodologies for STR analysis, the challenges in interpreting STR variations across different populations, and the implications of STRs in medical genetics. Our findings underscore the urgent need for comprehensive STR databases that reflect the genetic diversity of global populations, facilitating the interpretation of STR data in clinical diagnostics, genetic research, and forensic applications. This work sets the stage for future studies aimed at harnessing STR variations to elucidate complex genetic traits and diseases, reinforcing the importance of integrating STRs into genetic research and clinical practice.

Diagnostic evaluation of patients with epileptic spasms in the era of next-generation sequencing.

Epileptic spasms (ES) can be caused by a variety of etiologies. However, in almost half of cases, the etiology is unidentified. With the advent of next-generation sequencing (NGS), the recognition of genetic etiologies has increased. We retrospectively reviewed the medical records of patients with ES who were evaluated in the comprehensive epilepsy program at King Fahad Specialist Hospital Dammam between 2009 and 2022. Our data show that in 57.7% of patients with ES, the etiology was unidentified after a standard clinical evaluation and neuroimaging. Of these patients, n = 25 (35.2%) received a genetic diagnosis after some form of genetic testing, and 3.1% of patients from specialized metabolic work indicated the need for genetic testing to confirm the diagnosis. Karyotyping led to a diagnosis in 3.6% of patients, and chromosomal microarray led to a diagnosis in 7.1%. An NGS epilepsy gene panel (EP) was done for 45 patients, leading to a diagnosis in 24.4% (n = 11). Exome sequencing was done for 27 patients, including n = 14 with non-diagnostic panel testing; it led to a diagnosis in 37.3% (n = 10). Exome sequencing led to a diagnosis in 61.5% of patients without a previous panel test and in only two patients who had previously had a negative panel testing. In this article, we present the diagnostic evaluations of ES for a cohort of 123 patients and discuss the yield and priority of NGS for evaluating ES. Our findings suggest that exome sequencing has a higher diagnostic yield for determining the etiology of ES in patients for whom the etiology is still unclear after an appropriate clinical assessment and a brain MRI.

Optimization of Fluorescence In Situ Hybridization Protocols in the Era of Precision Medicine.

Fluorescence in situ hybridization (FISH) is a cytogenetic assay that is widely used in both clinical and research settings to validate genetic aberrations. Simple in principle, it is based on denaturation and hybridization of a DNA probe and its complementary sequence; however, it is subject to continuous optimization. Here we share how in-house FISH can be optimized using different control tissues to visualize and ultimately validate common and novel genetic abnormalities unearthed by next-generation sequencing (NGS). Seven specific FISH probes were designed and labeled, and conditions for eight tissue types and one patient-derived tumor organoid were optimized. Formalin-fixed paraffin-embedded (FFPE) tissue slides were used for each experiment. Slides were first deparaffinized, then placed in a pretreatment solution followed by a digestion step. In-house FISH probes were then added to the tissue to be denatured and hybridized, and then washed twice. To obtain optimal results, probe concentration, pepsin incubation time, denaturation, and the two post-hybridization washes were optimized for each sample. By modifying the above conditions, all FISH experiments were optimized in separate tissue types to investigate specific genomic alterations in tumors arising in those tissues. Signals were clear and distinct, allowing for visualization of the selected probes. Following this protocol, our lab has quickly optimized 11 directly labeled in-house FISH probes to support genetic aberrations nominated by NGS, including most recent discoveries through whole-genome sequencing analyses. We describe a robust approach of how to advance in-house labeled FISH probes. By following these guidelines, reliable and reproducible FISH results can be obtained to interrogate FFPE slides from benign, tumor tissues, and patient-derived tumor organoid specimens. This is of most relevance in the era of NGS and precision oncology. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Metaphase FISH optimization Support Protocol 1: In-house probe labeling and preparation Support Protocol 2: Metaphase spread preparation Basic Protocol 2: Optimization of FISH on formalin-fixed paraffin-embedded tissue.

The Utility of Genetic Testing in Infantile Epileptic Spasms Syndrome: A Step-Based Approach in the Next-Generation Sequencing Era

BackgroundTo evaluate the utility of genetic testing for etiology-specific diagnosis (ESD) in infantile epileptic spasms syndrome (IESS) with a step-based diagnostic approach in the next-generation sequencing (NGS) era. MethodsThe study cohort consisted of 314 patients with IESS, followed by the Pediatric Neurology Division of Ege University Hospital between 2005 and 2021. The ESD was evaluated using a step-based approach: step I (clinical phenomenology), step II (neuroimaging), step III (metabolic screening), and step IV (genetic testing). The diagnostic utility of genetic testing was evaluated to compare the early-NGS period (2005 to 2013, n = 183) and the NGS era (2014 to 2021, n = 131). ResultsAn ESD was established in 221 of 314 (70.4%) infants with IESS: structural, 40.8%; genetic, 17.2%; metabolic, 8.3%; immune-infectious, 4.1%. The diagnostic yield of genetic testing increased from 8.9% to 41.7% in the cohort during the four follow-up periods. The rate of unknown etiology decreased from 34.9% to 22.1% during the follow-up periods. The genetic ESD was established as 27.4% with genetic testing in the NGS era. The genetic testing in the NGS era increased dramatically in subgroups with unknown and structural etiologies. The diagnostic yields of the epilepsy panels increased from 7.6% to 19.2%. However, the diagnostic yield of whole exome sequencing remained at similar levels during the early-NGS period at 54.5% and in the NGS era at 59%. ConclusionsThe more genetic ESD (27.4%) was defined for IESS in the NGS era with the implication of precision therapy (37.7%).

Variants of Unknown Significance in Maturity-Onset Diabetes of the Young: High Rate of Conundrum Resolution via Variants of Unknown Significance Reanalysis

Introduction: In the era of next-generation sequencing, clinicians frequently encounter variants of unknown significance (VUS) in genetic testing. VUS may be reclassified over time as genetic knowledge grows. We know little about how best to approach VUS in the maturity-onset diabetes of the young (MODY). Therefore, our study aimed to determine the utility of reanalysis of previous VUS results in genetic confirmation of MODY. Methods: A single-center retrospective chart review identified 85 subjects with a MODY clinical diagnosis. We reanalyzed genetic testing in 10 subjects with 14 unique VUS on MODY genes that was performed >3 years before the study. Demographic, clinical, and biochemical data was collected for those individuals. Results: After reanalysis, 43% (6/14) of the gene variants were reclassified to a different category: 7% (1/14) were “likely pathogenic” and 36% (5/14) were “benign” or “likely benign.” The reclassified pathogenic variant was in HNF1A and all reclassified benign variants were in HNF1A, HNF1B and PDX1. The median time between MODY testing and reclassification was 8 years (range: 4–10 years). Conclusion: In sum, iterative reanalyzing the genetic data from VUS found during MODY testing may provide high-yield diagnostic information. Further studies are warranted to identify the optimal time and frequency for such analyses.

The utility of electrodiagnostic testing in unprovoked rhabdomyolysis in the era of next-generation sequencing.

Rhabdomyolysis is an etiologically heterogeneous, acute necrosis of myofibers characterized by transient marked creatine kinase (CK) elevation associated with myalgia, muscle edema, and/or weakness. The study aimed to determine the role of electrodiagnostic (EDX) testing relative to genetic testing and muscle biopsy in patients with unprovoked rhabdomyolysis in identifying an underlying myopathy. EDX database was reviewed to identify unprovoked rhabdomyolysis patients who underwent EDX testing between January 2012 and January 2022. Each patient's clinical profile, EDX findings, muscle pathology, laboratory, and genetic testing results were analyzed. Of 66 patients identified, 32 had myopathic electromyography (EMG). Muscle biopsy and genetic testing were performed in 41 and 37 patients, respectively. A definitive diagnosis was achieved in 15 patients (11 myopathic EMG and 4 nonmyopathic EMG; p = .04) based on abnormal muscle biopsy (4/11 patients) or genetic testing (12/12 patients, encompassing 5 patients with normal muscle biopsy and 3 patients with nonmyopathic EMG). These included seven metabolic and eight nonmetabolic myopathies (five muscular dystrophies and three ryanodine receptor 1 [RYR1]-myopathies). Patients were more likely to have baseline weakness (p < .01), elevated baseline CK (p < .01), and nonmetabolic myopathies (p = .03) when myopathic EMG was identified. Myopathic EMG occurred in approximately half of patients with unprovoked rhabdomyolysis, more likely in patients with weakness and elevated CK at baseline. Although patients with myopathic EMG were more likely to have nonmetabolic myopathies, nonmyopathic EMG did not exclude myopathy, and genetic testing was primarily helpful to identify an underlying myopathy. Genetic testing should likely be first-tier diagnostic testing following unprovoked rhabdomyolysis.

Digital counting of tissue cells for molecular analysis: the QuANTUM pipeline.

The estimation of tumor cellular fraction (TCF) is a crucial step in predictive molecular pathology, representing an entry adequacy criterion also in the next-generation sequencing (NGS) era. However, heterogeneity of quantification practices and inter-pathologist variability hamper the robustness of its evaluation, stressing the need for more reliable results. Here, 121 routine histological samples from non-small cell lung cancer (NSCLC) cases with complete NGS profiling were used to evaluate TCF interobserver variability among three different pathologists (pTCF), developing a computational tool (cTCF) and assessing its reliability vs ground truth (GT) tumor cellularity and potential impact on the final molecular results. Inter-pathologist reproducibility was fair to good, with overall Wk ranging between 0.46 and 0.83 (avg. 0.59). The obtained cTCF was comparable to the GT (p = 0.129, 0.502, and 0.130 for surgical, biopsies, and cell block, respectively) and demonstrated good reliability if elaborated by different pathologists (Wk = 0.9). Overall cTCF was lower as compared to pTCF (30 ± 10 vs 52 ± 19, p < 0.001), with more cases < 20% (17, 14%, p = 0.690), but none containing < 100 cells for the algorithm. Similarities were noted between tumor area estimation and pTCF (36 ± 29, p < 0.001), partly explaining variability in the human assessment of tumor cellularity. Finally, the cTCF allowed a reduction of the copy number variations (CNVs) called (27 vs 29, - 6.9%) with an increase of effective CNVs detection (13 vs 7, + 85.7%), some with potential clinical impact previously undetected with pTCF. An automated computational pipeline (Qupath Analysis of Nuclei from Tumor to Uniform Molecular tests, QuANTUM) has been created and is freely available as a QuPath extension. The computational method used in this study has the potential to improve efficacy and reliability of TCF estimation in NSCLC, with demonstrated impact on the final molecular results.

The genetic landscape of mitochondrial diseases in the next-generation sequencing era: a Portuguese cohort study.

Introduction: Rare disorders that are genetically and clinically heterogeneous, such as mitochondrial diseases (MDs), have a challenging diagnosis. Nuclear genes codify most proteins involved in mitochondrial biogenesis, despite all mitochondria having their own DNA. The development of next-generation sequencing (NGS) technologies has revolutionized the understanding of many genes involved in the pathogenesis of MDs. In this new genetic era, using the NGS approach, we aimed to identify the genetic etiology for a suspected MD in a cohort of 450 Portuguese patients. Methods: We examined 450 patients using a combined NGS strategy, starting with the analysis of a targeted mitochondrial panel of 213 nuclear genes, and then proceeding to analyze the whole mitochondrial DNA. Results and Discussion: In this study, we identified disease-related variants in 134 (30%) analyzed patients, 88 with nuclear DNA (nDNA) and 46 with mitochondrial DNA (mtDNA) variants, most of them being pediatric patients (66%), of which 77% were identified in nDNA and 23% in mtDNA. The molecular analysis of this cohort revealed 72 already described pathogenic and 20 novel, probably pathogenic, variants, as well as 62 variants of unknown significance. For this cohort of patients with suspected MDs, the use of a customized gene panel provided a molecular diagnosis in a timely and cost-effective manner. Patients who cannot be diagnosed after this initial approach will be further selected for whole-exome sequencing. Conclusion: As a national laboratory for the study and research of MDs, we demonstrated the power of NGS to achieve a molecular etiology, expanding the mutational spectrum and proposing accurate genetic counseling in this group of heterogeneous diseases without therapeutic options.

Considerations for Familial Chylomicronemia Diagnosis in the Era of Next-Generation Sequencing: A Latin American Perspective

Considerations for Familial Chylomicronemia Diagnosis in the Era of Next-Generation Sequencing: A Latin American Perspective

Does Neonatal Microbiome Research Encompass the Placental Transfer Pathway?

The word “microbiome” is a combination of “microbiota” and “genome,” which represents the genomic concept of microbiota. The bacterial culture method is the mainstay of identifying microbes, while polymerase chain reaction adds diagnostic value. However, in the era of next-generation sequencing, achieving high-throughput microbiota footprints is extremely sensitive. This sensitivity often leads to confusion, as it can detect specific microbes genomes, even in sterile samples, such as blood, placenta, breast milk, skin, vagina, and stool. The neonatal microbiome remarkably influences both fetal and neonatal life related to health status and disease outcome. However, its origins pose a question: does it stem from a direct gateway or through a breakdown of barriers? This review provides a brief overview of evidence and speculative insights.

Statistical learning quantifies transposable element-mediated cis-regulation

BackgroundTransposable elements (TEs) have colonized the genomes of most metazoans, and many TE-embedded sequences function as cis-regulatory elements (CREs) for genes involved in a wide range of biological processes from early embryogenesis to innate immune responses. Because of their repetitive nature, TEs have the potential to form CRE platforms enabling the coordinated and genome-wide regulation of protein-coding genes by only a handful of trans-acting transcription factors (TFs).ResultsHere, we directly test this hypothesis through mathematical modeling and demonstrate that differences in expression at protein-coding genes alone are sufficient to estimate the magnitude and significance of TE-contributed cis-regulatory activities, even in contexts where TE-derived transcription fails to do so. We leverage hundreds of overexpression experiments and estimate that, overall, gene expression is influenced by TE-embedded CREs situated within approximately 500 kb of promoters. Focusing on the cis-regulatory potential of TEs within the gene regulatory network of human embryonic stem cells, we find that pluripotency-specific and evolutionarily young TE subfamilies can be reactivated by TFs involved in post-implantation embryogenesis. Finally, we show that TE subfamilies can be split into truly regulatorily active versus inactive fractions based on additional information such as matched epigenomic data, observing that TF binding may better predict TE cis-regulatory activity than differences in histone marks.ConclusionOur results suggest that TE-embedded CREs contribute to gene regulation during and beyond gastrulation. On a methodological level, we provide a statistical tool that infers TE-dependent cis-regulation from RNA-seq data alone, thus facilitating the study of TEs in the next-generation sequencing era.

Novel alleles in the era of next-generation sequencing-based HLA typing calls for standardization and policy.

Next-Generation Sequencing (NGS) has transformed clinical histocompatibility laboratories through its capacity to provide accurate, high-throughput, high-resolution typing of Human Leukocyte Antigen (HLA) genes, which is critical for transplant safety and success. As this technology becomes widely used for clinical genotyping, histocompatibility laboratories now have an increased capability to identify novel HLA alleles that previously would not be detected using traditional genotyping methods. Standard guidelines for the clinical verification and reporting of novelties in the era of NGS are greatly needed. Here, we describe the experience of a clinical histocompatibility laboratory's use of NGS for HLA genotyping and its management of novel alleles detected in an ethnically-diverse population of British Columbia, Canada. Over a period of 18months, 3,450 clinical samples collected for the purpose of solid organ or hematopoietic stem cell transplantation were sequenced using NGS. Overall, 29 unique novel alleles were identified at a rate of ∼1.6 per month. The majority of novelties (52%) were detected in the alpha chains of class II (HLA-DQA1 and -DPA1). Novelties were found in all 11 HLA classical genes except for HLA-DRB3, -DRB4, and -DQB1. All novelties were single nucleotide polymorphisms, where more than half led to an amino acid change, and one resulted in a premature stop codon. Missense mutations were evaluated for changes in their amino acid properties to assess the potential effect on the novel HLA protein. All novelties identified were confirmed independently at another accredited HLA laboratory using a different NGS assay and platform to ensure validity in the reporting of novelties. The novel alleles were submitted to the Immuno Polymorphism Database-Immunogenetics/HLA (IPD-IMGT/HLA) for official allele name designation and inclusion in future database releases. A nationwide survey involving all Canadian HLA laboratories confirmed the common occurrence of novel allele detection but identified a wide variability in the assessment and reporting of novelties. In summary, a considerable proportion of novel alleles were identified in routine clinical testing. We propose a framework for the standardization of policies on the clinical management of novel alleles and inclusion in proficiency testing programs in the era of NGS-based HLA genotyping.

BCR::ABL1-negative myeloproliferative neoplasms in the era of next-generation sequencing.

The classical BCR::ABL1-negative myeloproliferative neoplasms such as polycythemia vera (PV), essential thrombocythemia (ET), and myelofibrosis (MF) are clonal diseases with the presence of characteristic "driver mutations" in one of the genes: JAK2, CALR, or MPL. The search for mutations in these three genes is required for the diagnosis of MPNs. Nevertheless, the progress that has been made in the field of molecular genetics has opened a new era in medicine. The search for additional mutations in MPNs is helpful in assessing the risk stratification, disease progression, transformation to acute myeloid leukemia (AML), or choosing the right treatment. In some cases, advanced technologies are needed to find a clonal marker of the disease and establish a diagnosis. This review focuses on how the use of new technologies like next-generation sequencing (NGS) helps in the diagnosis of BCR::ABL1-negative myeloproliferative neoplasms.

Pangenome insights into the diversification and disease specificity of worldwide Xanthomonas outbreaks.

The bacterial genus Xanthomonas is responsible for disease outbreaks in several hundred plant species, many of them economically important crops. In the era of next-generation sequencing, thousands of strains from this genus have now been sequenced as part of isolated studies that focus on outbreak characterization, host range, diversity, and virulence factor identification. However, these data have not been synthesized and we lack a comprehensive phylogeny for the genus, with some species designations in public databases still relying on phenotypic similarities and representative sequence typing. The extent of genetic cohesiveness among Xanthomonas strains, the distribution of virulence factors across strains, and the impact of evolutionary history on host range across the genus are also poorly understood. In this study, we present a pangenome analysis of 1,910 diverse Xanthomonas genomes, highlighting their evolutionary relationships, the distribution of virulence-associated genes across strains, and rates of horizontal gene transfer. We find a number of broadly conserved classes of virulence factors and considerable diversity in the Type 3 Secretion Systems (T3SSs) and Type 3 Secreted Effector (T3SE) repertoires of different Xanthomonas species. We also use these data to re-assign incorrectly classified strains to phylogenetically informed species designations and find evidence of both monophyletic host specificity and convergent evolution of phylogenetically distant strains to the same host. Finally, we explore the role of recombination in maintaining genetic cohesion within the Xanthomonas genus as a result of both ancestral and recent recombination events. Understanding the evolutionary history of Xanthomonas species and the relationship of key virulence factors with host-specificity provides valuable insight into the mechanisms through which Xanthomonas species shift between hosts and will enable us to develop more robust resistance strategies against these highly virulent pathogens.

1281-P: Variants of Unknown Significance (VUS) in Maturity-Onset Diabetes of the Young (MODY)—High Rate of Conundrum Resolution via Reanalysis of VUS

In the era of next-generation sequencing, clinicians frequently encounter VUS on genetic tests for MODY. Pathogenicity ascertainment of those variants may have substantial impact on optimal diabetes care. We aimed to determine the usefulness of reanalyzing previous VUS results in MODY. We performed a retrospective chart review to identify subjects with a VUS on a MODY genetic test performed &amp;gt; 3 years before the study and requested reanalysis of their genetic data at Athena Diagnostics. We identified 10 subjects with at least one VUS on MODY genetic testing (mean age at diagnosis: 13.4 ± 3.4 years, 60% female, 60% Hispanic, 20% African American and 20% non-Hispanic White). After reanalysis, 50% were recategorized to a different category: 30% “likely pathogenic” and 20% “benign”. All newly reclassified pathogenic variants were in HNF1A, and benign variants were in HNF1B and PDX1. The median time to reclassification since MODY testing was 8 years (range 4-10 years). The mean random C-peptide at diagnosis was 1.17 ± 0.17, 2.24 ± 0.8 and 2.96 ± 1.4 ng/mL for those with variants reclassified as benign, likely pathogenic and those who remained as VUS, respectively. In sum, periodic reanalysis of the genetic data of cases with a VUS on MODY tests may provide high-yield diagnostic information. Further studies are warranted to identify the optimal time and frequency for such analyses. Disclosure G.Alarcon: None. M.J.Redondo: None. M.Tosur: Advisory Panel; Provention Bio, Inc.