Transcriptional analysis of muscle tissue and isolated satellite cells in spastic cerebral palsy.

AIM: To analyze transcriptomes from muscle tissue and cells to improve our understanding of differences in gene expression and molecular function in cerebral palsy (CP) muscle. METHOD: In this case-control study, eight participants with CP (five males, three females; mean [SD] age 14y 2mo [1y 8mo]) and 11 comparison individuals (eight males, three females; mean [SD] age 14y 0mo [2y 6mo]) were enrolled after informed consent/assent and skeletal muscle was obtained during surgery. RNA was extracted from tissue and from primary satellite cells grown to form myotubes in vitro. RNA sequencing data were analyzed using validated informatics pipelines. RESULTS: Analysis identified expression of 6308 genes in the tissue samples and 7459 in the cultured cells. Significant differential expression between CP and control was identified in 87 genes in the tissue and 90 genes in isolated satellite cell-derived myotube cultures. INTERPRETATION: Both tissue and cell analyses identified differential expression of genes associated with muscle development and multiple pathways of interest. What this paper adds Expression differences were found in muscle tissue and in isolated muscle cells. There was low variability in expression among cells isolated from different muscles. Expression differences suggest complex functional alterations in spastic cerebral palsy.

Protein S-Nitrosylation Controls Glycogen Synthase Kinase 3ß Function Independent of Its Phosphorylation State.

RATIONALE: GSK-3ß (glycogen synthase kinase 3ß) is a multifunctional and constitutively active kinase known to regulate a myriad of cellular processes. The primary mechanism to regulate its function is through phosphorylation-dependent inhibition at serine-9 residue. Emerging evidence indicates that there may be alternative mechanisms that control GSK-3ß for certain functions. OBJECTIVES: Here, we sought to understand the role of protein S-nitrosylation (SNO) on the function of GSK-3ß. SNO-dependent modulation of the localization of GSK-3ß and its ability to phosphorylate downstream targets was investigated in vitro, and the network of proteins differentially impacted by phospho- or SNO-dependent GSK-3ß regulation and in vivo SNO modification of key signaling kinases during the development of heart failure was also studied. METHODS AND RESULTS: We found that GSK-3ß undergoes site-specific SNO both in vitro, in HEK293 cells, H9C2 myoblasts, and primary neonatal rat ventricular myocytes, as well as in vivo, in hearts from an animal model of heart failure and sudden cardiac death. S-nitrosylation of GSK-3ß significantly inhibits its kinase activity independent of the canonical phospho-inhibition pathway. S-nitrosylation of GSK-3ß promotes its nuclear translocation and access to novel downstream phosphosubstrates which are enriched for a novel amino acid consensus sequence motif. Quantitative phosphoproteomics pathway analysis reveals that nuclear GSK-3ß plays a central role in cell cycle control, RNA splicing, and DNA damage response. CONCLUSIONS: The results indicate that SNO has a differential effect on the location and activity of GSK-3ß in the cytoplasm versus the nucleus. SNO modification of GSK-3ß occurs in vivo and could contribute to the pathobiology of heart failure and sudden cardiac death.

Mapping Citrullinated Sites in Multiple Organs of Mice Using Hypercitrullinated Library.

Protein citrullination (or deimination), an irreversible post-translational modification, has been implicated in several physiological and pathological processes, including gene expression regulation, apoptosis, rheumatoid arthritis, and Alzheimer's disease. Several research studies have been carried out on citrullination under many conditions. However, until now, challenges in sample preparation and data analysis have made it difficult to confidently identify a citrullinated protein and assign the citrullinated site. To overcome these limitations, we generated a mouse hyper-citrullinated spectral library and set up coordinates to confidently identify and validate citrullinated sites. Using this workflow, we detect a four-fold increase in citrullinated proteome coverage across six mouse organs compared with the current state-of-the art techniques. Our data reveal that the subcellular distribution of citrullinated proteins is tissue-type-dependent and that citrullinated targets are involved in fundamental physiological processes, including the metabolic process. These data represent the first report of a hyper-citrullinated library for the mouse and serve as a central resource for exploring the role of citrullination in this organism.

Epigenetic machine learning: utilizing DNA methylation patterns to predict spastic cerebral palsy.

BACKGROUND: Spastic cerebral palsy (CP) is a leading cause of physical disability. Most people with spastic CP are born with it, but early diagnosis is challenging, and no current biomarker platform readily identifies affected individuals. The aim of this study was to evaluate epigenetic profiles as biomarkers for spastic CP. A novel analysis pipeline was employed to assess DNA methylation patterns between peripheral blood cells of adolescent subjects (14.9 ± 0.3 years old) with spastic CP and controls at single CpG site resolution. RESULTS: Significantly hypo- and hyper-methylated CpG sites associated with spastic CP were identified. Nonmetric multidimensional scaling fully discriminated the CP group from the controls. Machine learning based classification modeling indicated a high potential for a diagnostic model, and 252 sets of 40 or fewer CpG sites achieved near-perfect accuracy within our adolescent cohorts. A pilot test on significantly younger subjects (4.0 ± 1.5 years old) identified subjects with 73% accuracy. CONCLUSIONS: Adolescent patients with spastic CP can be distinguished from a non-CP cohort based on DNA methylation patterns in peripheral blood cells. A clinical diagnostic test utilizing a panel of CpG sites may be possible using a simulated classification model. A pilot validation test on patients that were more than 10 years younger than the main adolescent cohorts indicated that distinguishing methylation patterns are present earlier in life. This study is the first to report an epigenetic assay capable of distinguishing a CP cohort.

Subphenotype meta-analysis of testicular cancer genome-wide association study data suggests a role for RBFOX family genes in cryptorchidism susceptibility.

STUDY QUESTION: Can subphenotype analysis of genome-wide association study (GWAS) data from subjects with testicular germ cell tumor (TGCT) provide insight into cryptorchidism (undescended testis, UDT) susceptibility? SUMMARY ANSWER: Suggestive intragenic GWAS signals common to UDT, TGCT case-case and TGCT case-control analyses occur in genes encoding RBFOX RNA-binding proteins (RBPs) and their neurodevelopmental targets. WHAT IS KNOWN ALREADY: UDT is a strong risk factor for TGCT, but while genetic risk factors for TGCT are well-known, genetic susceptibility to UDT is poorly understood and appears to be more complex. STUDY DESIGN, SIZE, DURATION: We performed a secondary subphenotype analysis of existing GWAS data from the Testicular Cancer Consortium (TECAC) and compared these results with our previously published UDT GWAS data, and with data previously acquired from studies of the fetal rat gubernaculum. PARTICIPANTS/MATERIALS, SETTING, METHODS: Studies from the National Cancer Institute (NCI), United Kingdom (UK) and University of Pennsylvania (Penn) that enrolled white subjects were the source of the TGCT GWAS data. We completed UDT subphenotype case-case (TGCT/UDT vs TGCT/non-UDT) and case-control (TGCT/UDT vs control), collectively referred to as 'TECAC' analyses, followed by a meta-analysis comprising 129 TGCT/UDT cases, 1771 TGCT/non-UDT cases, and 3967 unaffected controls. We reanalyzed our UDT GWAS results comprising 844 cases and 2718 controls by mapping suggestive UDT and TECAC signals (defined as P < 0.001) to genes using Ingenuity Pathway Analysis (IPA®). We compared associated pathways and enriched gene categories common to all analyses after Benjamini-Hochberg multiple testing correction, and analyzed transcript levels and protein expression using qRT-PCR and rat fetal gubernaculum confocal imaging, respectively. MAIN RESULTS AND THE ROLE OF CHANCE: We found suggestive signals within 19 genes common to all three analyses, including RBFOX1 and RBFOX3, neurodevelopmental paralogs that encode RBPs targeting (U)GCATG-containing transcripts. Ten of the 19 genes participate in neurodevelopment and/or contribute to risk of neurodevelopmental disorders. Experimentally predicted RBFOX gene targets were strongly overrepresented among suggestive intragenic signals for the UDT (117 of 628 (19%), P = 3.5 × 10-24), TECAC case-case (129 of 711 (18%), P = 2.5 × 10-27) and TECAC case-control (117 of 679 (17%), P = 2 × 10-21) analyses, and a majority of the genes common to all three analyses (12 of 19 (63%), P = 3 × 10-9) are predicted RBFOX targets. Rbfox1, Rbfox2 and their encoded proteins are expressed in the rat fetal gubernaculum. Predicted RBFOX targets are also enriched among transcripts differentially regulated in the fetal gubernaculum during normal development (P = 3 × 10-31), in response to in vitro hormonal stimulation (P = 5 × 10-45) and in the cryptorchid LE/orl rat (P = 2 × 10-42). LARGE SCALE DATA: GWAS data included in this study are available in the database of Genotypes and Phenotypes (dbGaP accession numbers phs000986.v1.p1 and phs001349.v1p1). LIMITATIONS, REASONS FOR CAUTION: These GWAS data did not reach genome-wide significance for any individual analysis. UDT appears to have a complex etiology that also includes environmental factors, and such complexity may require much larger sample sizes than are currently available. The current methodology may also introduce bias that favors false discovery of larger genes. WIDER IMPLICATIONS OF THE FINDINGS: Common suggestive intragenic GWAS signals suggest that RBFOX paralogs and other neurodevelopmental genes are potential UDT risk candidates, and potential TGCT susceptibility modifiers. Enrichment of predicted RBFOX targets among differentially expressed transcripts in the fetal gubernaculum additionally suggests a role for this RBP family in regulation of testicular descent. As RBFOX proteins regulate alternative splicing of Calca to generate calcitonin gene-related peptide, a protein linked to development and function of the gubernaculum, additional studies that address the role of these proteins in UDT are warranted. STUDY FUNDING/COMPETING INTEREST(S): The Eunice Kennedy Shriver National Institute for Child Health and Human Development (R01HD060769); National Center for Research Resources (P20RR20173), National Institute of General Medical Sciences (P20GM103464), Nemours Biomedical Research, the Testicular Cancer Consortium (U01CA164947), the Intramural Research Program of the NCI, a support services contract HHSN26120130003C with IMS, Inc., the Abramson Cancer Center at Penn, National Cancer Institute (CA114478), the Institute of Cancer Research, UK and the Wellcome Trust Case-Control Consortium (WTCCC) 2. None of the authors reports a conflict of interest.

Dual Labeling Biotin Switch Assay to Reduce Bias Derived From Different Cysteine Subpopulations: A Method to Maximize S-Nitrosylation Detection.

RATIONALE: S-nitrosylation (SNO), an oxidative post-translational modification of cysteine residues, responds to changes in the cardiac redox-environment. Classic biotin-switch assay and its derivatives are the most common methods used for detecting SNO. In this approach, the labile SNO group is selectively replaced with a single stable tag. To date, a variety of thiol-reactive tags have been introduced. However, these methods have not produced a consistent data set, which suggests an incomplete capture by a single tag and potentially the presence of different cysteine subpopulations. OBJECTIVE: To investigate potential labeling bias in the existing methods with a single tag to detect SNO, explore if there are distinct cysteine subpopulations, and then, develop a strategy to maximize the coverage of SNO proteome. METHODS AND RESULTS: We obtained SNO-modified cysteine data sets for wild-type and S-nitrosoglutathione reductase knockout mouse hearts (S-nitrosoglutathione reductase is a negative regulator of S-nitrosoglutathione production) and nitric oxide-induced human embryonic kidney cell using 2 labeling reagents: the cysteine-reactive pyridyldithiol and iodoacetyl based tandem mass tags. Comparison revealed that <30% of the SNO-modified residues were detected by both tags, whereas the remaining SNO sites were only labeled by 1 reagent. Characterization of the 2 distinct subpopulations of SNO residues indicated that pyridyldithiol reagent preferentially labels cysteine residues that are more basic and hydrophobic. On the basis of this observation, we proposed a parallel dual-labeling strategy followed by an optimized proteomics workflow. This enabled the profiling of 493 SNO sites in S-nitrosoglutathione reductase knockout hearts. CONCLUSIONS: Using a protocol comprising 2 tags for dual-labeling maximizes overall detection of SNO by reducing the previously unrecognized labeling bias derived from different cysteine subpopulations.

Protein kinase G signaling in cardiac pathophysiology: Impact of proteomics on clinical trials.

The protective role of cyclic guanosine monophosphate (cGMP)-stimulated protein kinase G (PKG) in the heart makes it an attractive target for therapeutic drug development to treat a variety of cardiac diseases. Phosphodiesterases degrade cGMP, thus phosphodiesterase inhibitors that can increase PKG are of translational interest and the subject of ongoing human trials. PKG signaling is complex, however, and understanding its downstream phosphorylation targets and upstream regulation are necessary steps toward safe and efficacious drug development. Proteomic technologies have paved the way for assays that allow us to peer broadly into signaling minutia, including protein quantity changes and phosphorylation events. However, there are persistent challenges to the proteomic study of PKG, such as the impact of the expression of different PKG isoforms, changes in its localization within the cell, and alterations caused by oxidative stress. PKG signaling is also dependent upon sex and potentially the genetic and epigenetic background of the individual. Thus, the rigorous application of proteomics to the field will be necessary to address how these effectors can alter PKG signaling and interfere with pharmacological interventions. This review will summarize PKG signaling, how it is being targeted clinically, and the proteomic challenges and techniques that are being used to study it.

KMT2A-D pathogenicity, prevalence, and variation according to a population database.

INTRODUCTION: The KMT2 family of genes is essential epigenetic regulators promoting gene expression. The gene family contains three subgroups, each with two paralogues: KMT2A and KMT2B; KMT2C and KMT2D; KMT2F and KMT2G. KMT2A-D are among the most frequent somatically altered genes in several different cancer types. Somatic KMT2A rearrangements are well-characterized in infant leukemia (IL), and growing evidence supports the role of additional family members (KMT2B, KMT2C, and KMT2D) in leukemogenesis. Enrichment of rare heterozygous frameshift variants in KMT2A and C has been reported in acute myeloid leukemia (AML), IL, and solid tumors. Currently, the non-synonymous variation, prevalence, and penetrance of these four genes are unknown. METHODS: This study determined the prevalence of pathogenic/likely pathogenic (P/LP) germline KMT2A-D variants in a cancer-free adult population from the Genome Aggregation Database (gnomAD). Two methods of variant interpretation were utilized: a manual genomic variant interpretation and an automated ACMG pipeline. RESULTS: The ACMG pipeline identified considerably fewer P/LP variants (n = 89) compared to the manual method (n = 660) in all 4 genes. Consequently, the total P/LP prevalence and allele frequency (AF) were higher in the manual method (1:112, AF = 4.46E-03) than in ACMG (1:832, AF = 6.01E-04). Multiple ancestry-exclusive P/LP variants were identified along with an increased frequency in males compared to females. Many of these variants identified in this population database are also associated with severe juvenile conditions. CONCLUSION: These data demonstrate that putatively functional germline variation in these developmentally important genes is more common than previously appreciated and identification in cancer-free adults may indicate incomplete penetrance for many of these variants. Future research should examine a genetic predisposing role in IL and other pediatric cancers.

Machine learning classifier approaches for predicting response to RTK-type-III inhibitors demonstrate high accuracy using transcriptomic signatures and ex vivo data.

Motivation: The application of machine learning (ML) techniques in the medical field has demonstrated both successes and challenges in the precision medicine era. The ability to accurately classify a subject as a potential responder versus a nonresponder to a given therapy is still an active area of research pushing the field to create new approaches for applying machine-learning techniques. In this study, we leveraged publicly available data through the BeatAML initiative. Specifically, we used gene count data, generated via RNA-seq, from 451 individuals matched with ex vivo data generated from treatment with RTK-type-III inhibitors. Three feature selection techniques were tested, principal component analysis, Shapley Additive Explanation (SHAP) technique and differential gene expression analysis, with three different classifiers, XGBoost, LightGBM and random forest (RF). Sensitivity versus specificity was analyzed using the area under the curve (AUC)-receiver operating curves (ROCs) for every model developed. Results: Our work demonstrated that feature selection technique, rather than the classifier, had the greatest impact on model performance. The SHAP technique outperformed the other feature selection techniques and was able to with high accuracy predict outcome response, with the highest performing model: Foretinib with 89% AUC using the SHAP technique and RF classifier. Our ML pipelines demonstrate that at the time of diagnosis, a transcriptomics signature exists that can potentially predict response to treatment, demonstrating the potential of using ML applications in precision medicine efforts. Availability and implementation: https://github.com/UD-CRPL/RCDML. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

Impact of Early Feeding: Metagenomics Analysis of the Infant Gut Microbiome.

Background: Different feeding regimens in infancy alter the gastrointestinal (gut) microbial environment. The fecal microbiota in turn influences gastrointestinal homeostasis including metabolism, immune function, and extra-/intra-intestinal signaling. Advances in next generation sequencing (NGS) have enhanced our ability to study the gut microbiome of breast-fed (BF) and formula-fed (FF) infants with a data-driven hypothesis approach. Methods: Next generation sequencing libraries were constructed from fecal samples of BF (n=24) and FF (n=10) infants and sequenced on an Illumina HiSeq 2500. Taxonomic classification of the NGS data was performed using the Sunbeam/Kraken pipeline and a functional analysis at the gene level was performed using publicly available algorithms, including BLAST, and custom scripts. Differentially represented genera, genes, and NCBI Clusters of Orthologous Genes (COG) were determined between cohorts using count data and R (statistical packages edgeR and DESeq2). Results: Thirty-nine genera were found to be differentially represented between the BF and FF cohorts (FDR ≤ 0.01) including Parabacteroides, Enterococcus, Haemophilus, Gardnerella, and Staphylococcus. A Welch t-test of the Shannon diversity index for BF and FF samples approached significance (p=0.061). Bray-Curtis and Jaccard distance analyses demonstrated clustering and overlap in each analysis. Sixty COGs were significantly overrepresented and those most significantly represented in BF vs. FF samples showed dichotomy of categories representing gene functions. Over 1,700 genes were found to be differentially represented (abundance) between the BF and FF cohorts. Conclusions: Fecal samples analyzed from BF and FF infants demonstrated differences in microbiota genera. The BF cohort includes greater presence of beneficial genus Bifidobacterium. Several genes were identified as present at different abundances between cohorts indicating differences in functional pathways such as cellular defense mechanisms and carbohydrate metabolism influenced by feeding. Confirmation of gene level NGS data via PCR and electrophoresis analysis revealed distinct differences in gene abundances associated with important biologic pathways.

Genomic surveillance of SARS-CoV-2 in the state of Delaware reveals tremendous genomic diversity.

The use of next generation sequencing is critical for the surveillance of severe acute respiratory syndrome coronavirus 2, SARS-CoV-2, transmission, as single base mutations have been identified with differences in infectivity. A total of 1,459 high quality samples were collected, sequenced, and analyzed in the state of Delaware, a location that offers a unique perspective on transmission given its proximity to large international airports on the east coast. Pangolin and Nextclade were used to classify these sequences into 16 unique clades and 88 lineages. A total of 411 samples belonging to the Alpha 20I/501Y.V1 (B.1.1.7) strain of concern were identified, as well as one sample belonging to Beta 20H/501.V2 (B.1.351), thirteen belonging to Epsilon 20C/S:452R (B.1.427/B.1.429), two belonging to Delta 20A/S:478K (B.1.617.2), and 15 belonging to Gamma 20J/501Y.V3 (p.1). A total of 2217 unique coding mutations were observed with an average of 17.7 coding mutations per genome. These data paired with continued sample collection and sequencing will give a deeper understanding of the spread of SARS-CoV-2 strains within Delaware and its surrounding areas.

CD24 Expression Dampens the Basal Antiviral State in Human Neuroblastoma Cells and Enhances Permissivity to Zika Virus Infection.

Zika virus (ZIKV) exhibits distinct selectivity for infection of various cells and tissues, but how host cellular factors modulate varying permissivity remains largely unknown. Previous studies showed that the neuroblastoma cell line SK-N-AS (expressing low levels of cellular protein CD24) was highly restricted for ZIKV infection, and that this restriction was relieved by ectopic expression of CD24. We tested the hypothesis that CD24 expression allowed ZIKV replication by suppression of the antiviral response. SK-N-AS cells expressing an empty vector (termed CD24-low cells) showed elevated basal levels of phosphorylated STAT1, IRF-1, IKKE, and NFκB. In response to exogenously added type I interferon (IFN-I), CD24-low cells had higher-level induction of antiviral genes and activity against two IFN-I-sensitive viruses (VSV and PIV5-P/V) compared to SK-N-AS cells with ectopic CD24 expression (termed CD24-high cells). Media-transfer experiments showed that the inherent antiviral state of CD24-low cells was not dependent on a secreted factor such as IFN-I. Transcriptomics analysis revealed that CD24 expression decreased expression of genes involved in intracellular antiviral pathways, including IFN-I, NFκB, and Ras. Our findings that CD24 expression in neuroblastoma cells represses intracellular antiviral pathways support the proposal that CD24 may represent a novel biomarker in cancer cells for susceptibility to oncolytic viruses.

DNA Methylation Analysis Reveals Distinct Patterns in Satellite Cell-Derived Myogenic Progenitor Cells of Subjects with Spastic Cerebral Palsy.

Spastic type cerebral palsy (CP) is a complex neuromuscular disorder that involves altered skeletal muscle microanatomy and growth, but little is known about the mechanisms contributing to muscle pathophysiology and dysfunction. Traditional genomic approaches have provided limited insight regarding disease onset and severity, but recent epigenomic studies indicate that DNA methylation patterns can be altered in CP. Here, we examined whether a diagnosis of spastic CP is associated with intrinsic DNA methylation differences in myoblasts and myotubes derived from muscle resident stem cell populations (satellite cells; SCs). Twelve subjects were enrolled (6 CP; 6 control) with informed consent/assent. Skeletal muscle biopsies were obtained during orthopedic surgeries, and SCs were isolated and cultured to establish patient-specific myoblast cell lines capable of proliferation and differentiation in culture. DNA methylation analyses indicated significant differences at 525 individual CpG sites in proliferating SC-derived myoblasts (MB) and 1774 CpG sites in differentiating SC-derived myotubes (MT). Of these, 79 CpG sites were common in both culture types. The distribution of differentially methylated 1 Mbp chromosomal segments indicated distinct regional hypo- and hyper-methylation patterns, and significant enrichment of differentially methylated sites on chromosomes 12, 13, 14, 15, 18, and 20. Average methylation load across 2000 bp regions flanking transcriptional start sites was significantly different in 3 genes in MBs, and 10 genes in MTs. SC derived MBs isolated from study participants with spastic CP exhibited fundamental differences in DNA methylation compared to controls at multiple levels of organization that may reveal new targets for studies of mechanisms contributing to muscle dysregulation in spastic CP.

Integrated stem cell signature and cytomolecular risk determination in pediatric acute myeloid leukemia.

Relapsed or refractory pediatric acute myeloid leukemia (AML) is associated with poor outcomes and relapse risk prediction approaches have not changed significantly in decades. To build a robust transcriptional risk prediction model for pediatric AML, we perform RNA-sequencing on 1503 primary diagnostic samples. While a 17 gene leukemia stem cell signature (LSC17) is predictive in our aggregated pediatric study population, LSC17 is no longer predictive within established cytogenetic and molecular (cytomolecular) risk groups. Therefore, we identify distinct LSC signatures on the basis of AML cytomolecular subtypes (LSC47) that were more predictive than LSC17. Based on these findings, we build a robust relapse prediction model within a training cohort and then validate it within independent cohorts. Here, we show that LSC47 increases the predictive power of conventional risk stratification and that applying biomarkers in a manner that is informed by cytomolecular profiling outperforms a uniform biomarker approach.

A research agenda to support the development and implementation of genomics-based clinical informatics tools and resources.

OBJECTIVE: The Genomic Medicine Working Group of the National Advisory Council for Human Genome Research virtually hosted its 13th genomic medicine meeting titled "Developing a Clinical Genomic Informatics Research Agenda". The meeting's goal was to articulate a research strategy to develop Genomics-based Clinical Informatics Tools and Resources (GCIT) to improve the detection, treatment, and reporting of genetic disorders in clinical settings. MATERIALS AND METHODS: Experts from government agencies, the private sector, and academia in genomic medicine and clinical informatics were invited to address the meeting's goals. Invitees were also asked to complete a survey to assess important considerations needed to develop a genomic-based clinical informatics research strategy. RESULTS: Outcomes from the meeting included identifying short-term research needs, such as designing and implementing standards-based interfaces between laboratory information systems and electronic health records, as well as long-term projects, such as identifying and addressing barriers related to the establishment and implementation of genomic data exchange systems that, in turn, the research community could help address. DISCUSSION: Discussions centered on identifying gaps and barriers that impede the use of GCIT in genomic medicine. Emergent themes from the meeting included developing an implementation science framework, defining a value proposition for all stakeholders, fostering engagement with patients and partners to develop applications under patient control, promoting the use of relevant clinical workflows in research, and lowering related barriers to regulatory processes. Another key theme was recognizing pervasive biases in data and information systems, algorithms, access, value, and knowledge repositories and identifying ways to resolve them.

The PNPLA3 rs738409 Variant but not MBOAT7 rs641738 is a Risk Factor for Nonalcoholic Fatty Liver Disease in Obese U.S. Children of Hispanic Ethnicity.

PURPOSE: The rs641738 C>T in membrane-bound O-acyltransferase domain-containing protein 7 (MBOAT7) is implicated, along with the rs738409 C>G polymorphism in patatin-like phospholipase domain-containing protein 3 (PNPLA3), in nonalcoholic fatty liver disease (NAFLD). The association of these polymorphisms and NAFLD are investigated in Hispanic children with obesity. METHODS: Obese children with and without NAFLD were enrolled at a pediatric tertiary care health system and genotyped for MBOAT7 rs641738 C>T and PNPLA3 rs738409 C>G. NAFLD was characterized by the ultrasonographic presence of hepatic steatosis along with persistently elevated liver enzymes. Genetic variants and demographic and biochemical data were analyzed for the effects on NAFLD. RESULTS: Among 126 enrolled subjects, 84 in the case group had NAFLD and 42 in the control group did not. The two groups had similar demographic distribution. NAFLD was associated with abnormal liver enzymes and elevated triglycerides and cholesterol (p<0.05). Children with NAFLD had higher percentage of PNPLA3 GG genotype at 70.2% versus 31.0% in non-NAFLD, and lower MBOAT7 TT genotype at 4.8% versus 16.7% in non-NAFLD (p<0.05). PNPLA3 rs738409 C>G had an additive effect in NAFLD; however, MBOAT7 rs641738 C>T had no effects alone or synergistically with PNPLA3 polymorphism. NAFLD risk increased 3.7-fold in subjects carrying PNPLA3 GG genotype and decreased in MBOAT7 TT genotype. CONCLUSION: In Hispanic children with obesity, PNPLA3 rs738409 C>G polymorphism increased the risk for NAFLD. The role of MBOAT7 rs641738 variant in NAFLD is less evident.

Accelerating next generation sequencing data analysis: an evaluation of optimized best practices for Genome Analysis Toolkit algorithms.

Advancements in next generation sequencing (NGS) technologies have significantly increased the translational use of genomics data in the medical field as well as the demand for computational infrastructure capable processing that data. To enhance the current understanding of software and hardware used to compute large scale human genomic datasets (NGS), the performance and accuracy of optimized versions of GATK algorithms, including Parabricks and Sentieon, were compared to the results of the original application (GATK V4.1.0, Intel x86 CPUs). Parabricks was able to process a 50× whole-genome sequencing library in under 3 h and Sentieon finished in under 8 h, whereas GATK v4.1.0 needed nearly 24 h. These results were achieved while maintaining greater than 99% accuracy and precision compared to stock GATK. Sentieon's somatic pipeline achieved similar results greater than 99%. Additionally, the IBM POWER9 CPU performed well on bioinformatic workloads when tested with 10 different tools for alignment/mapping.

Perspectives on Molecular Diagnostic Testing for the COVID-19 Pandemic in Delaware.

The United States has quickly transitioned into one of the epicenters for the coronavirus pandemic. Limitations for rapid testing for the virus responsible for the pandemic, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is the single most important barrier for early detection and prevention of future outbreaks. Combining innovative molecular biology techniques, such as clustered regularly interspaced short palindromic repeats (CRISPR)/Cas nuclease systems and next generation sequencing (NGS) may prove to be an effective solution to establish a high-throughput diagnostic and genomic surveillance workflow for COVID-19 in the State of Delaware. Integrating key expertise across the medical institutions in Delaware, including ChristianaCare and Nemours/Alfred I. duPont Hospital for Children, is one potential solution for overcoming current barriers and driving a successful implementation of these techniques.

Error-corrected sequencing strategies enable comprehensive detection of leukemic mutations relevant for diagnosis and minimal residual disease monitoring.

BACKGROUND: Pediatric leukemias have a diverse genomic landscape associated with complex structural variants, including gene fusions, insertions and deletions, and single nucleotide variants. Routine karyotype and fluorescence in situ hybridization (FISH) techniques lack sensitivity for smaller genomic alternations. Next-generation sequencing (NGS) assays are being increasingly utilized for assessment of these various lesions. However, standard NGS lacks quantitative sensitivity for minimal residual disease (MRD) surveillance due to an inherently high error rate. METHODS: Primary bone marrow samples from pediatric leukemia (n = 32) and adult leukemia subjects (n = 5), cell line MV4-11, and an umbilical cord sample were utilized for this study. Samples were sequenced using molecular barcoding with targeted DNA and RNA library enrichment techniques based on anchored multiplexed PCR (AMP®) technology, amplicon based error-corrected sequencing (ECS) or a human cancer transcriptome assay. Computational analyses were performed to quantitatively assess limit of detection (LOD) for various DNA and RNA lesions, which could be systematically used for MRD assays. RESULTS: Matched leukemia patient samples were analyzed at three time points; diagnosis, end of induction (EOI), and relapse. Similar to flow cytometry for ALL MRD, the LOD for point mutations by these sequencing strategies was ≥0.001. For DNA structural variants, FLT3 internal tandem duplication (ITD) positive cell line and patient samples showed a LOD of ≥0.001 in addition to previously unknown copy number losses in leukemia genes. ECS in RNA identified multiple novel gene fusions, including a SPANT-ABL gene fusion in an ALL patient, which could have been used to alter therapy. Collectively, ECS for RNA demonstrated a quantitative and complex landscape of RNA molecules with 12% of the molecules representing gene fusions, 12% exon duplications, 8% exon deletions, and 68% with retained introns. Droplet digital PCR validation of ECS-RNA confirmed results to single mRNA molecule quantities. CONCLUSIONS: Collectively, these assays enable a highly sensitive, comprehensive, and simultaneous analysis of various clonal leukemic mutations, which can be tracked across disease states (diagnosis, EOI, and relapse) with a high degree of sensitivity. The approaches and results presented here highlight the ability to use NGS for MRD tracking.

Strong concordance between RNA structural and single nucleotide variants identified via next generation sequencing techniques in primary pediatric leukemia and patient-derived xenograft samples.

Acute leukemia represents the most common pediatric malignancy comprising diverse subtypes with varying prognosis and treatment outcomes. New and targeted treatment options are warranted for this disease. Patient-derived xenograft (PDX) models are increasingly being used for preclinical testing of novel treatment modalities. A novel approach involving targeted error-corrected RNA sequencing using ArcherDX HemeV2 kit was employed to compare 25 primary pediatric acute leukemia samples and their corresponding PDX samples. A comparison of the primary samples and PDX samples revealed a high concordance between single nucleotide variants and gene fusions whereas other complex structural variants were not as consistent. The presence of gene fusions representing the major driver mutations at similar allelic frequencies in PDX samples compared to primary samples and over multiple passages confirms the utility of PDX models for preclinical drug testing. Characterization and tracking of these novel cryptic fusions and exonal variants in PDX models is critical in assessing response to potential new therapies.