Rhabditid Nematode-Associated Ophthalmitis and Meningoencephalomyelitis in Captive Asian Horned Frogs (\u3ci\u3eMegophrys montana\u3c/i\u3e) [Case reports]

Between 2006 and 2008, 4 captive Asian horned frogs (Megophrys montana) were diagnosed with ocular and neurologic disease associated with rhabditid nematodiasis. Mortality, either spontaneous or by humane euthanasia, was high (3/4, 75%). Gross and histologic findings included varying degrees of ulcerative keratitis, histiocytic uveitis and retinitis, meningoencephalomyelitis, and epidermal chromatophore (iridophore) hyperplasia with intralesional nematodes. Entry into the host was presumed to be by direct invasion of the skin and the cornea with migration through the optic nerve to the brain and spinal cord. One frog was diagnosed with rhabditid nematodiasis antemortem, and clinical signs and lesions in the frog did not progress after unilateral enucleation and anthelminthic treatment were completed. Gross and tissue morphology of the nematodes were consistent with the order Rhabditida. DNA was extracted separately from 2 individual nematodes that were isolated from frozen and ethanol-preserved eye and brain tissue. These DNA templates were used for polymerase chain reaction amplification and sequencing of nuclear 28S large subunit (LSD) and internal transcribed spacer (ITS) ribosomal DNA regions. Comparison of the LSD and ITS sequences to those deposited in GenBank revealed an exact match for Caenorhabditis elegans

Integrated genomics of susceptibility to alkylator-induced leukemia in mice

<p>Abstract</p> <p>Background</p> <p>Therapy-related acute myeloid leukemia (t-AML) is a secondary, generally incurable, malignancy attributable to chemotherapy exposure. Although there is a genetic component to t-AML susceptibility in mice, the relevant loci and the mechanism(s) by which they contribute to t-AML are largely unknown. An improved understanding of susceptibility factors and the biological processes in which they act may lead to the development of t-AML prevention strategies.</p> <p>Results</p> <p>In this work we applied an integrated genomics strategy in inbred strains of mice to find novel factors that might contribute to susceptibility. We found that the pre-exposure transcriptional state of hematopoietic stem/progenitor cells predicts susceptibility status. More than 900 genes were differentially expressed between susceptible and resistant strains and were highly enriched in the apoptotic program, but it remained unclear which genes, if any, contribute directly to t-AML susceptibility. To address this issue, we integrated gene expression data with genetic information, including single nucleotide polymorphisms (SNPs) and DNA copy number variants (CNVs), to identify genetic networks underlying t-AML susceptibility. The 30 t-AML susceptibility networks we found are robust: they were validated in independent, previously published expression data, and different analytical methods converge on them. Further, the networks are enriched in genes involved in cell cycle and DNA repair (pathways not discovered in traditional differential expression analysis), suggesting that these processes contribute to t-AML susceptibility. Within these networks, the putative regulators (e.g., <it>Parp2</it>, <it>Casp9</it>, <it>Polr1b</it>) are the most likely to have a non-redundant role in the pathogenesis of t-AML. While identifying these networks, we found that current CNVR and SNP-based haplotype maps in mice represented distinct sources of genetic variation contributing to expression variation, implying that mapping studies utilizing either source alone will have reduced sensitivity.</p> <p>Conclusion</p> <p>The identification and prioritization of genes and networks not previously implicated in t-AML generates novel hypotheses on the biology and treatment of this disease that will be the focus of future research.</p

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Peer reviewe

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

Preparedness of the CTSA's Structural and Scientific Assets to Support the Mission of the National Center for Advancing Translational Sciences (NCATS)

The formation of the National Center for Advancing Translational Sciences (NCATS) brings new promise for moving basic and discoveries to clinical practice, ultimately improving the health of the nation. The CTSA sites, now housed with NCATS, are organized and prepared to support in this endeavor. The CTSAs provide a foundation for capitalizing on such promise through provision of a disease-agnostic infrastructure devoted to C&T science, maintenance of training programs designed for C&T investigators of the future, by incentivizing institutional reorganization and by cultivating institutional support