Evaluation of DNA Methylation Episignatures for Diagnosis and Phenotype Correlations in 42 Mendelian Neurodevelopmental Disorders.

Genetic syndromes frequently present with overlapping clinical features and inconclusive or ambiguous genetic findings which can confound accurate diagnosis and clinical management. An expanding number of genetic syndromes have been shown to have unique genomic DNA methylation patterns (called episignatures ). Peripheral blood episignatures can be used for diagnostic testing as well as for the interpretation of ambiguous genetic test results. We present here an approach to episignature mapping in 42 genetic syndromes, which has allowed the identification of 34 robust disease-specific episignatures. We examine emerging patterns of overlap, as well as similarities and hierarchical relationships across these episignatures, to highlight their key features as they are related to genetic heterogeneity, dosage effect, unaffected carrier status, and incomplete penetrance. We demonstrate the necessity of multiclass modeling for accurate genetic variant classification and show how disease classification using a single episignature at a time can sometimes lead to classification errors in closely related episignatures. We demonstrate the utility of this tool in resolving ambiguous clinical cases and identification of previously undiagnosed cases through mass screening of a large cohort of subjects with developmental delays and congenital anomalies. This study more than doubles the number of published syndromes with DNA methylation episignatures and, most significantly, opens new avenues for accurate diagnosis and clinical assessment in individuals affected by these disorders

Impact of intensive care unit supportive care on the physiology of Ebola virus disease in a universally lethal non-human primate model

Abstract Background There are currently limited data for the use of specific antiviral therapies for the treatment of Ebola virus disease (EVD). While there is anecdotal evidence that supportive care may be effective, there is a paucity of direct experimental data to demonstrate a role for supportive care in EVD. We studied the impact of ICU-level supportive care interventions including fluid resuscitation, vasoactive medications, blood transfusion, hydrocortisone, and ventilator support on the pathophysiology of EVD in rhesus macaques infected with a universally lethal dose of Ebola virus strain Makona C07. Methods Four NHPs were infected with a universally lethal dose Ebola virus strain Makona, in accordance with the gold standard lethal Ebola NHP challenge model. Following infection, the following therapeutic interventions were employed: continuous bedside supportive care, ventilator support, judicious fluid resuscitation, vasoactive medications, blood transfusion, and hydrocortisone as needed to treat cardiovascular compromise. A range of physiological parameters were continuously monitored to gage any response to the interventions. Results All four NHPs developed EVD and demonstrated a similar clinical course. All animals reached a terminal endpoint, which occurred at an average time of 166.5 ± 14.8 h post-infection. Fluid administration may have temporarily blunted a rise in lactate, but the effect was short lived. Vasoactive medications resulted in short-lived improvements in mean arterial pressure. Blood transfusion and hydrocortisone did not appear to have a significant positive impact on the course of the disease. Conclusions The model employed for this study is reflective of an intramuscular infection in humans (e.g., needle stick) and is highly lethal to NHPs. Using this model, we found that the animals developed progressive severe organ dysfunction and profound shock preceding death. While the overall impact of supportive care on the observed pathophysiology was limited, we did observe some time-dependent positive responses. Since this model is highly lethal, it does not reflect the full spectrum of human EVD. Our findings support the need for continued development of animal models that replicate the spectrum of human disease as well as ongoing development of anti-Ebola therapies to complement supportive care

Correction to: Impact of intensive care unit supportive care on the physiology of Ebola virus disease in a universally lethal non-human primate model

Please note that four authors (Logan Banadyga, Alixandra Albietz, Brad Pickering, and Gary Wong) have been erroneously omitted from the author list in the published original article [1]

Characterization of Ebola Virus Risk to Bedside Providers in an Intensive Care Environment

Background: The 2014–2016 Ebola outbreak in West Africa recapitulated that nosocomial spread of Ebola virus could occur and that health care workers were at particular risk including notable cases in Europe and North America. These instances highlighted the need for centers to better prepare for potential Ebola virus cases; including understanding how the virus spreads and which interventions pose the greatest risk. Methods: We created a fully equipped intensive care unit (ICU), within a Biosafety Level 4 (BSL4) laboratory, and infected multiple sedated non-human primates (NHPs) with Ebola virus. While providing bedside care, we sampled blood, urine, and gastric residuals; as well as buccal, ocular, nasal, rectal, and skin swabs, to assess the risks associated with routine care. We also assessed the physical environment at end-point. Results: Although viral RNA was detectable in blood as early as three days post-infection, it was not detectable in the urine, gastric fluid, or swabs until late-stage disease. While droplet spread and fomite contamination were present on a few of the surfaces that were routinely touched while providing care in the ICU for the infected animal, these may have been abrogated through good routine hygiene practices. Conclusions: Overall this study has helped further our understanding of which procedures may pose the highest risk to healthcare providers and provides temporal evidence of this over the clinical course of disease

Evaluation of DNA Methylation Episignatures for Diagnosis and Phenotype Correlations in 42 Mendelian Neurodevelopmental Disorders

Genetic syndromes frequently present with overlapping clinical features and inconclusive or ambiguous genetic findings which can confound accurate diagnosis and clinical management. An expanding number of genetic syndromes have been shown to have unique genomic DNA methylation patterns (called “episignatures”). Peripheral blood episignatures can be used for diagnostic testing as well as for the interpretation of ambiguous genetic test results. We present here an approach to episignature mapping in 42 genetic syndromes, which has allowed the identification of 34 robust disease-specific episignatures. We examine emerging patterns of overlap, as well as similarities and hierarchical relationships across these episignatures, to highlight their key features as they are related to genetic heterogeneity, dosage effect, unaffected carrier status, and incomplete penetrance. We demonstrate the necessity of multiclass modeling for accurate genetic variant classification and show how disease classification using a single episignature at a time can sometimes lead to classification errors in closely related episignatures. We demonstrate the utility of this tool in resolving ambiguous clinical cases and identification of previously undiagnosed cases through mass screening of a large cohort of subjects with developmental delays and congenital anomalies. This study more than doubles the number of published syndromes with DNA methylation episignatures and, most significantly, opens new avenues for accurate diagnosis and clinical assessment in individuals affected by these disorders

Erratum: Evaluation of DNA Methylation Episignatures for Diagnosis and Phenotype Correlations in 42 Mendelian Neurodevelopmental Disorders (The American Journal of Human Genetics (2020) 106(3) (356–370), (S0002929720300197), (10.1016/j.ajhg.2020.01.019))

(The American Journal of Human Genetics 106, 356–370; March 5, 2020) In the version of this paper originally published, the underlying cause for Hunter McAlpine syndrome was incorrectly described in Table 1. The relevant description has been changed to read “Chr5q35-qter duplication involving NSD1” in the updated Table 1 reflected here. The authors apologize for this error