Electrical and Electronic Engineering - Research Publications
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ItemPredicting the diagnosis of autism spectrum disorder using gene pathway analysis(NATURE PUBLISHING GROUP, 2014-04)Autism spectrum disorder (ASD) depends on a clinical interview with no biomarkers to aid diagnosis. The current investigation interrogated single-nucleotide polymorphisms (SNPs) of individuals with ASD from the Autism Genetic Resource Exchange (AGRE) database. SNPs were mapped to Kyoto Encyclopedia of Genes and Genomes (KEGG)-derived pathways to identify affected cellular processes and develop a diagnostic test. This test was then applied to two independent samples from the Simons Foundation Autism Research Initiative (SFARI) and Wellcome Trust 1958 normal birth cohort (WTBC) for validation. Using AGRE SNP data from a Central European (CEU) cohort, we created a genetic diagnostic classifier consisting of 237 SNPs in 146 genes that correctly predicted ASD diagnosis in 85.6% of CEU cases. This classifier also predicted 84.3% of cases in an ethnically related Tuscan cohort; however, prediction was less accurate (56.4%) in a genetically dissimilar Han Chinese cohort (HAN). Eight SNPs in three genes (KCNMB4, GNAO1, GRM5) had the largest effect in the classifier with some acting as vulnerability SNPs, whereas others were protective. Prediction accuracy diminished as the number of SNPs analyzed in the model was decreased. Our diagnostic classifier correctly predicted ASD diagnosis with an accuracy of 71.7% in CEU individuals from the SFARI (ASD) and WTBC (controls) validation data sets. In conclusion, we have developed an accurate diagnostic test for a genetically homogeneous group to aid in early detection of ASD. While SNPs differ across ethnic groups, our pathway approach identified cellular processes common to ASD across ethnicities. Our results have wide implications for detection, intervention and prevention of ASD.
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ItemNo Preview AvailablePan-Family Assays for Rapid Viral Screening: Reducing Delays in Public Health Responses During Pandemics(OXFORD UNIV PRESS INC, 2021-11-01)BACKGROUND: Coronavirus disease 2019 has highlighted deficiencies in the testing capacity of many developed countries during the early stages of pandemics. Here we describe a strategy using pan-family viral assays to improve early accessibility of large-scale nucleic acid testing. METHODS: Coronaviruses and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were used as a case study for assessing utility of pan-family viral assays during the early stages of a novel pandemic. Specificity of a pan-coronavirus (Pan-CoV) assay for a novel pathogen was assessed using the frequency of common human coronavirus (HCoV) species in key populations. A reported Pan-CoV assay was assessed to determine sensitivity to 60 reference coronaviruses, including SARS-CoV-2. The resilience of the primer target regions of this assay to mutation was assessed in 8893 high-quality SARS-CoV-2 genomes to predict ongoing utility during pandemic progression. RESULTS: Because of common HCoV species, a Pan-CoV assay would return false positives for as few as 1% of asymptomatic adults, but up to 30% of immunocompromised patients with respiratory disease. One-half of reported Pan-CoV assays identify SARS-CoV-2 and with small adjustments can accommodate diverse variation observed in animal coronaviruses. The target region of 1 well-established Pan-CoV assay is highly resistant to mutation compared to species-specific SARS-CoV-2 reverse transcriptase-polymerase chain reaction assays. CONCLUSIONS: Despite cross-reactivity with common pathogens, pan-family assays may greatly assist management of emerging pandemics through prioritization of high-resolution testing or isolation measures. Targeting highly conserved genomic regions make pan-family assays robust and resilient to mutation. A strategic stockpile of pan-family assays may improve containment of novel diseases before the availability of species-specific assays.