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Your search keyword '"Mary M Elfrink"' showing total 2 results
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2 results on '"Mary M Elfrink"'

1. Genomic answers for children: Dynamic analyses of >1000 pediatric rare disease genomes

Author

Ana S.A. Cohen, Emily G. Farrow, Ahmed T. Abdelmoity, Joseph T. Alaimo, Shivarajan M. Amudhavalli, John T. Anderson, Lalit Bansal, Lauren Bartik, Primo Baybayan, Bradley Belden, Courtney D. Berrios, Rebecca L. Biswell, Pawel Buczkowicz, Orion Buske, Shreyasee Chakraborty, Warren A. Cheung, Keith A. Coffman, Ashley M. Cooper, Laura A. Cross, Tom Curran, Thuy Tien T. Dang, Mary M. Elfrink, Kendra L. Engleman, Erin D. Fecske, Cynthia Fieser, Keely Fitzgerald, Emily A. Fleming, Randi N. Gadea, Jennifer L. Gannon, Rose N. Gelineau-Morel, Margaret Gibson, Jeffrey Goldstein, Elin Grundberg, Kelsee Halpin, Brian S. Harvey, Bryce A. Heese, Wendy Hein, Suzanne M. Herd, Susan S. Hughes, Mohammed Ilyas, Jill Jacobson, Janda L. Jenkins, Shao Jiang, Jeffrey J. Johnston, Kathryn Keeler, Jonas Korlach, Jennifer Kussmann, Christine Lambert, Caitlin Lawson, Jean-Baptiste Le Pichon, James Steven Leeder, Vicki C. Little, Daniel A. Louiselle, Michael Lypka, Brittany D. McDonald, Neil Miller, Ann Modrcin, Annapoorna Nair, Shelby H. Neal, Christopher M. Oermann, Donna M. Pacicca, Kailash Pawar, Nyshele L. Posey, Nigel Price, Laura M.B. Puckett, Julio F. Quezada, Nikita Raje, William J. Rowell, Eric T. Rush, Venkatesh Sampath, Carol J. Saunders, Caitlin Schwager, Richard M. Schwend, Elizabeth Shaffer, Craig Smail, Sarah Soden, Meghan E. Strenk, Bonnie R. Sullivan, Brooke R. Sweeney, Jade B. Tam-Williams, Adam M. Walter, Holly Welsh, Aaron M. Wenger, Laurel K. Willig, Yun Yan, Scott T. Younger, Dihong Zhou, Tricia N. Zion, Isabelle Thiffault, and Tomi Pastinen

Subjects
Genome, Rare Diseases, High-Throughput Nucleotide Sequencing, Humans, Genomics, Sequence Analysis, DNA, Child, Genetics (clinical), Pedigree
Abstract

This study aimed to provide comprehensive diagnostic and candidate analyses in a pediatric rare disease cohort through the Genomic Answers for Kids program.Extensive analyses of 960 families with suspected genetic disorders included short-read exome sequencing and short-read genome sequencing (srGS); PacBio HiFi long-read genome sequencing (HiFi-GS); variant calling for single nucleotide variants (SNV), structural variant (SV), and repeat variants; and machine-learning variant prioritization. Structured phenotypes, prioritized variants, and pedigrees were stored in PhenoTips database, with data sharing through controlled access the database of Genotypes and Phenotypes.Diagnostic rates ranged from 11% in patients with prior negative genetic testing to 34.5% in naive patients. Incorporating SVs from genome sequencing added up to 13% of new diagnoses in previously unsolved cases. HiFi-GS yielded increased discovery rate with4-fold more rare coding SVs compared with srGS. Variants and genes of unknown significance remain the most common finding (58% of nondiagnostic cases).Computational prioritization is efficient for diagnostic SNVs. Thorough identification of non-SNVs remains challenging and is partly mitigated using HiFi-GS sequencing. Importantly, community research is supported by sharing real-time data to accelerate gene validation and by providing HiFi variant (SNV/SV) resources from1000 human alleles to facilitate implementation of new sequencing platforms for rare disease diagnoses.

Published
2022

2. IGenomic answers for children: Dynamic analyses of >1000 pediatric rare disease genomes

Author

Jill Jacobson, Keith A Coffman, Susan S Hughes, Caitlin Lawson, Erin D Fecske, Ahmed T Abdelmoity, Thuy Tien T Dang, Annapoorna Nair, Janda L Jenkins, Kendra L Engleman, Daniel A Louiselle, Orion Buske, Nigel Price, Dihong Zhou, Michael Lypka, Courtney D Berrios, Laura Mb Puckett, Kelsee Halpin, Ana Sa Cohen, Nikita Raje, Aaron M Wenger, Emily G Farrow, Keely Fitzgerald, Mohammed Ilyas, Kailash Pawar, Joseph T Alaimo, Jennifer L Gannon, Laurel K Willig, Jean-Baptiste Le Pichon, Shivarajan M Amudhavalli, Christopher M Oermann, Rebecca L Biswell, Shelby H Neal, Lalit Bansal, Elizabeth Shaffer, Brittany D McDonald, Bonnie R Sullivan, Isabelle Thiffault, Christine Lambert, Ashley M Cooper, Suzanne M Herd, Holly Welsh, Julio F Quezada, Carol J Saunders, Caitlin Schwager, Brian S Harvey, Adam M Walter, Donna M Pacicca, Jennifer Kussmann, Rose N Gelineau-Morel, Margaret Gibson, Elin Grundberg, Shao Jiang, Scott T Younger, Steve Leeder, Richard M Schwend, John T Anderson, Venkatesh Sampath, Jonas Korlach, Bryce A Heese, Meghan E Strenk, Neil Miller, Vicki C Little, Ann Modrcin, Brooke R Sweeney, Randi N Gadea, Nyshele L Posey, Emily A Fleming, Wendy Hein, Cynthia Fieser, Eric T Rush, Laura A Cross, Craig Smail, William J Rowell, Kathryn Keeler, Jeffrey Goldstein, Tricia N Zion, Warren A. Cheung, Sarah Soden, Lauren Bartik, Bradley Belden, Thomas Curran, Pawel Buczkowicz, Shreyasee Chakraborty, Yun Yan, Tomi Pastinen, Primo Baybayan, Mary M Elfrink, Jeffrey J Johnston, and Jade B Tam-Williams

Subjects
Unknown Significance, Pedigree chart, Computational biology, Allele, Biology, Gene, Genome, Exome, DNA sequencing, Rare disease
Abstract

PURPOSETo provide comprehensive diagnostic and candidate analyses in a pediatric rare disease cohort through the Genomic Answers for Kids (GA4K) program.METHODSExtensive analyses of 960 families with suspected genetic disorders including short-read exome (ES) and genome sequencing (srGS); PacBio HiFi long-read GS (HiFi-GS); variant calling for small-nucleotide (SNV), structural (SV) and repeat variants; and machine-learning variant prioritization. Structured phenotypes, prioritized variants and pedigrees are stored in PhenoTips database, with data sharing through controlled access (dbGAP).RESULTSDiagnostic rates ranged from 11% for cases with prior negative genetic tests to 34.5% in naïve patients. Incorporating SVs from GS added up to 13% of new diagnoses in previously unsolved cases. HiFi-GS yielded increased discovery rate with >4-fold more rare coding SVs than srGS. Variants and genes of unknown significance (VUS/GUS) remain the most common finding (58% of non-diagnostic cases).CONCLUSIONComputational prioritization is efficient for diagnostic SNVs. Thorough identification of non-SNVs remains challenging and is partly mitigated by HiFi-GS sequencing. Importantly, community research is supported by sharing real-time data to accelerate gene validation, and by providing HiFi variant (SNV/SV) resources from >1,000 human alleles to facilitate implementation of new sequencing platforms for rare disease diagnoses.

Published
2021

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