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Vanoye CG, Desai RR, John JD, Hoffman SC, Fink N, Zhang Y, Venkatesh OG, Roe J, Adusumilli S, Jairam NP, Sanders CR, Gordon AS, George AL. Functional profiling of KCNE1 variants informs population carrier frequency of Jervell and Lange-Nielsen syndrome type 2. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.03.28.646046. [PMID: 40236191 PMCID: PMC11996308 DOI: 10.1101/2025.03.28.646046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/17/2025]
Abstract
Congenital long-QT syndrome (LQTS) is most often associated with pathogenic variants in KCNQ1 encoding the pore-forming voltage-gated potassium channel subunit of the slow delayed rectifier current ( I Ks ). Generation of I Ks requires assembly of KCNQ1 with an auxiliary subunit encoded by KCNE1 , which is also associated with LQTS but causality of autosomal dominant disease is disputed. By contrast, KCNE1 is an accepted cause of recessive type 2 Jervell and Lange-Nielson syndrome (JLN2). The functional consequences of most KCNE1 variants have not been determined and the population prevalence of JLN2 is unknown. Methods : We determined the functional properties of 95 KCNE1 variants co-expressed with KCNQ1 in heterologous cells using high-throughput voltage-clamp recording. Experiments were conducted with each KCNE1 variant expressed in the homozygous state and then a subset was studied in the heterozygous state. The carrier frequency of JLN2 was estimated by considering the population prevalence of dysfunctional variants. Results : There is substantial overlap between disease-associated and population KCNE1 variants. When examined in the homozygous state, 68 KCNE1 variants exhibited significant differences in at least one functional property compared to WT KCNE1, whereas 27 variants did not significantly affect function. Most dysfunctional variants exhibited loss-of-function properties. We observed no evidence of dominant-negative effects. Most variants were scored as variants of uncertain significance (VUS) and inclusion of functional data resulted in revised classifications for only 14 variants. The population carrier frequency of JLN2 was calculated as 1 in 1034. Peak current density and activation voltage-dependence but no other biophysical properties were correlated with findings from a mutational scan of KCNE1. Conclusions : Among 95 disease-associated or population KCNE1 variants, many exhibit abnormal functional properties but there was no evidence of dominant-negative behaviors. Using functional data, we inferred a population carrier frequency for recessive JLN2. This work helps clarify the pathogenicity of KCNE1 variants.
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Pedroza Matute S, Turvey K, Iyavoo S. Advancing human genotyping: The Infinium HTS iSelect Custom microarray panel (Rita) development study. Forensic Sci Int Genet 2024; 71:103049. [PMID: 38653142 DOI: 10.1016/j.fsigen.2024.103049] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 04/04/2024] [Accepted: 04/15/2024] [Indexed: 04/25/2024]
Abstract
Single Nucleotide Polymorphisms (SNPs), as the most prevalent type of variation in the human genome, play a pivotal role in influencing human traits. They are extensively utilized in diverse fields such as population genetics, forensic science, and genetic medicine. This study focuses on the 'Rita' BeadChip, a custom SNP microarray panel developed using Illumina Infinium HTS technology. Designed for high-throughput genotyping, the panel facilitates the analysis of over 4000 markers efficiently and cost-effectively. After careful clustering performed on a set of 1000 samples, an evaluation of the Rita panel was undertaken, assessing its sensitivity, repeatability, reproducibility, precision, accuracy, and resistance to contamination. The panel's performance was evaluated in various scenarios, including sex estimation and parental relationship assessment, using GenomeStudio data analysis software. Findings show that over 95 % of the custom BeadChip assay markers were successful, with better performance of transitions over other mutations, and a considerably lower success rate for Y chromosome loci. An exceptional call rate exceeding 99 % was demonstrated for control samples, even with DNA input as low as 0.781 ng. Call rates above 80 % were still obtained with DNA quantities under 0.1 ng, indicating high sensitivity and suitability for forensic applications where DNA quantity is often limited. Repeatability, reproducibility, and precision studies revealed consistency of the panel's performance across different batches and operators, with no significant deviations in call rates or genotyping results. Accuracy assessments, involving comparison with multiple available genetic databases, including the 1000 Genome Project and HapMap, denoted over 99 % concordance, establishing the Rita panel's reliability in genotyping. The contamination study revealed insights into background noise and allowed the definition of thresholds for sample quality evaluation. Multiple metrics for differentiating between negative controls and true samples were highlighted, increasing the reliability of the obtained results. The sex estimation tool in GenomeStudio proved highly effective, correctly assigning sex in all samples with autosomal loci call rates above 97 %. The parental relationship assessment of family trios highlighted the utility of GenomeStudio in identifying genotyping errors or potential Mendelian inconsistencies, promoting the application of arrays such as Rita in kinship testing. Overall, this evaluation confirms the Rita microarray as a robust, high-throughput genotyping tool, underscoring its potential in genetic research and forensic applications. With its custom content and adaptable design, it not only meets current genotyping demands but also opens avenues for further research and application expansion in the field of genetic analysis.
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Affiliation(s)
| | - Kiera Turvey
- IDna Genetics Limited, Scottow Enterprise Park, Norwich, Norfolk NR10 5FB, United Kingdom
| | - Sasitaran Iyavoo
- IDna Genetics Limited, Scottow Enterprise Park, Norwich, Norfolk NR10 5FB, United Kingdom; School of Chemistry, College of Health and Science, University of Lincoln, Lincoln, Lincolnshire LN6 7TS, United Kingdom.
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3
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O'Brien TD, Potter AB, Driscoll CC, Goh G, Letaw JH, McCabe S, Thanner J, Kulkarni A, Wong R, Medica S, Week T, Buitrago J, Larson A, Camacho KJ, Brown K, Crist R, Conrad C, Evans-Dutson S, Lutz R, Mitchell A, Anur P, Serrato V, Shafer A, Marriott LK, Hamman KJ, Mulford A, Wiszniewski W, Sampson JE, Adey A, O'Roak BJ, Harrington CA, Shannon J, Spellman PT, Richards CS. Population screening shows risk of inherited cancer and familial hypercholesterolemia in Oregon. Am J Hum Genet 2023; 110:1249-1265. [PMID: 37506692 PMCID: PMC10432140 DOI: 10.1016/j.ajhg.2023.06.014] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Revised: 06/28/2023] [Accepted: 06/29/2023] [Indexed: 07/30/2023] Open
Abstract
The Healthy Oregon Project (HOP) is a statewide effort that aims to build a large research repository and influence the health of Oregonians through providing no-cost genetic screening to participants for a next-generation sequencing 32-gene panel comprising genes related to inherited cancers and familial hypercholesterolemia. This type of unbiased population screening can detect at-risk individuals who may otherwise be missed by conventional medical approaches. However, challenges exist for this type of high-throughput testing in an academic setting, including developing a low-cost high-efficiency test and scaling up the clinical laboratory for processing large numbers of samples. Modifications to our academic clinical laboratory including efficient test design, robotics, and a streamlined analysis approach increased our ability to test more than 1,000 samples per month for HOP using only one dedicated HOP laboratory technologist. Additionally, enrollment using a HIPAA-compliant smartphone app and sample collection using mouthwash increased efficiency and reduced cost. Here, we present our experience three years into HOP and discuss the lessons learned, including our successes, challenges, opportunities, and future directions, as well as the genetic screening results for the first 13,670 participants tested. Overall, we have identified 730 pathogenic/likely pathogenic variants in 710 participants in 24 of the 32 genes on the panel. The carrier rate for pathogenic/likely pathogenic variants in the inherited cancer genes on the panel for an unselected population was 5.0% and for familial hypercholesterolemia was 0.3%. Our laboratory experience described here may provide a useful model for population screening projects in other states.
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Affiliation(s)
- Timothy D O'Brien
- Knight Diagnostic Laboratories, Oregon Health & Science University, Portland, OR 97239, USA
| | - Amiee B Potter
- Knight Diagnostic Laboratories, Oregon Health & Science University, Portland, OR 97239, USA
| | - Catherine C Driscoll
- Knight Diagnostic Laboratories, Oregon Health & Science University, Portland, OR 97239, USA; Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201, USA
| | - Gregory Goh
- Knight Diagnostic Laboratories, Oregon Health & Science University, Portland, OR 97239, USA; Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201, USA
| | - John H Letaw
- Knight Diagnostic Laboratories, Oregon Health & Science University, Portland, OR 97239, USA
| | - Sarah McCabe
- Knight Diagnostic Laboratories, Oregon Health & Science University, Portland, OR 97239, USA
| | - Jane Thanner
- Information Technology Group, Oregon Health & Science University, Portland, OR 97201, USA
| | - Arpita Kulkarni
- Knight Diagnostic Laboratories, Oregon Health & Science University, Portland, OR 97239, USA
| | - Rossana Wong
- Knight Diagnostic Laboratories, Oregon Health & Science University, Portland, OR 97239, USA
| | - Samuel Medica
- Integrated Genomics Laboratory, Oregon Health & Science University, Portland, OR 97239, USA
| | - Tiana Week
- Integrated Genomics Laboratory, Oregon Health & Science University, Portland, OR 97239, USA
| | - Jacob Buitrago
- Integrated Genomics Laboratory, Oregon Health & Science University, Portland, OR 97239, USA
| | - Aaron Larson
- Integrated Genomics Laboratory, Oregon Health & Science University, Portland, OR 97239, USA
| | - Katie Johnson Camacho
- Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201, USA
| | - Kim Brown
- Knight Cancer Institute, Community Outreach and Engagement, Oregon Health & Science University, Portland, OR 97201, USA
| | - Rachel Crist
- Knight Cancer Institute, Community Outreach and Engagement, Oregon Health & Science University, Portland, OR 97201, USA
| | - Casey Conrad
- Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201, USA
| | - Sara Evans-Dutson
- Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201, USA
| | - Ryan Lutz
- Knight Cancer Institute, Community Outreach and Engagement, Oregon Health & Science University, Portland, OR 97201, USA
| | - Asia Mitchell
- Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201, USA
| | - Pavana Anur
- Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201, USA
| | - Vanessa Serrato
- Knight Cancer Institute, Community Outreach and Engagement, Oregon Health & Science University, Portland, OR 97201, USA
| | - Autumn Shafer
- University of Oregon, School of Journalism and Communication, Portland, OR 97209, USA
| | | | - K J Hamman
- Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR 97239, USA
| | - Amelia Mulford
- Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR 97239, USA
| | - Wojciech Wiszniewski
- Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR 97239, USA
| | - Jone E Sampson
- Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR 97239, USA
| | - Andrew Adey
- Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201, USA; Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR 97239, USA
| | - Brian J O'Roak
- Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR 97239, USA
| | - Christina A Harrington
- Integrated Genomics Laboratory, Oregon Health & Science University, Portland, OR 97239, USA; Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR 97239, USA
| | - Jackilen Shannon
- Knight Cancer Institute, Community Outreach and Engagement, Oregon Health & Science University, Portland, OR 97201, USA; Division of Oncological Sciences, Oregon Health & Science University, Portland, OR 97239, USA
| | - Paul T Spellman
- Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201, USA; Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR 97239, USA
| | - C Sue Richards
- Knight Diagnostic Laboratories, Oregon Health & Science University, Portland, OR 97239, USA; Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR 97239, USA.
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4
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Felker SA, Lawlor JMJ, Hiatt SM, Thompson ML, Latner DR, Finnila CR, Bowling KM, Bonnstetter ZT, Bonini KE, Kelly NR, Kelley WV, Hurst ACE, Rashid S, Kelly MA, Nakouzi G, Hendon LG, Bebin EM, Kenny EE, Cooper GM. Poison exon annotations improve the yield of clinically relevant variants in genomic diagnostic testing. Genet Med 2023; 25:100884. [PMID: 37161864 PMCID: PMC10524927 DOI: 10.1016/j.gim.2023.100884] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 05/01/2023] [Accepted: 05/03/2023] [Indexed: 05/11/2023] Open
Abstract
PURPOSE Neurodevelopmental disorders (NDDs) often result from rare genetic variation, but genomic testing yield for NDDs remains below 50%, suggesting that clinically relevant variants may be missed by standard analyses. Here, we analyze "poison exons" (PEs), which are evolutionarily conserved alternative exons often absent from standard gene annotations. Variants that alter PE inclusion can lead to loss of function and may be highly penetrant contributors to disease. METHODS We curated published RNA sequencing data from developing mouse cortex to define 1937 conserved PE regions potentially relevant to NDDs, and we analyzed variants found by genome sequencing in multiple NDD cohorts. RESULTS Across 2999 probands, we found 6 novel clinically relevant variants in PE regions. Five of these variants are in genes that are part of the sodium voltage-gated channel alpha subunit family (SCN1A, SCN2A, and SCN8A), which is associated with epilepsies. One variant is in SNRPB, associated with cerebrocostomandibular syndrome. These variants have moderate to high computational impact assessments, are absent from population variant databases, and in genes with gene-phenotype associations consistent with each probands reported features. CONCLUSION With a very minimal increase in variant analysis burden (average of 0.77 variants per proband), annotation of PEs can improve diagnostic yield for NDDs and likely other congenital conditions.
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Affiliation(s)
| | | | - Susan M Hiatt
- HudsonAlpha Institute for Biotechnology, Huntsville, AL
| | | | | | | | | | | | - Katherine E Bonini
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Nicole R Kelly
- Division of Pediatric Genetic Medicine, Department of Pediatrics, Children's Hospital at Montefiore/Montefiore Medical Center/Albert Einstein College of Medicine, Bronx, NY
| | | | | | | | | | | | | | - E Martina Bebin
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL
| | - Eimear E Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY; Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
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5
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Felker SA, Lawlor JMJ, Hiatt SM, Thompson ML, Latner DR, Finnila CR, Bowling KM, Bonnstetter ZT, Bonini KE, Kelly NR, Kelley WV, Hurst ACE, Kelly MA, Nakouzi G, Hendon LG, Bebin EM, Kenny EE, Cooper GM. Poison exon annotations improve the yield of clinically relevant variants in genomic diagnostic testing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.12.523654. [PMID: 36711854 PMCID: PMC9882217 DOI: 10.1101/2023.01.12.523654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Purpose Neurodevelopmental disorders (NDDs) often result from rare genetic variation, but genomic testing yield for NDDs remains around 50%, suggesting some clinically relevant rare variants may be missed by standard analyses. Here we analyze "poison exons" (PEs) which, while often absent from standard gene annotations, are alternative exons whose inclusion results in a premature termination codon. Variants that alter PE inclusion can lead to loss-of-function and may be highly penetrant contributors to disease. Methods We curated published RNA-seq data from developing mouse cortex to define 1,937 PE regions conserved between humans and mice and potentially relevant to NDDs. We then analyzed variants found by genome sequencing in multiple NDD cohorts. Results Across 2,999 probands, we found six clinically relevant variants in PE regions that were previously overlooked. Five of these variants are in genes that are part of the sodium voltage-gated channel alpha subunit family ( SCN1A, SCN2A , and SCN8A ), associated with epilepsies. One variant is in SNRPB , associated with Cerebrocostomandibular Syndrome. These variants have moderate to high computational impact assessments, are absent from population variant databases, and were observed in probands with features consistent with those reported for the associated gene. Conclusion With only a minimal increase in variant analysis burden (most probands had zero or one candidate PE variants in a known NDD gene, with an average of 0.77 per proband), annotation of PEs can improve diagnostic yield for NDDs and likely other congenital conditions.
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Affiliation(s)
| | - James MJ Lawlor
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA 35806
| | - Susan M Hiatt
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA 35806
| | | | - Donald R Latner
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA 35806
| | | | - Kevin M Bowling
- Washington University School of Medicine, Saint Louis, MO, USA 63110
| | | | - Katherine E Bonini
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai. New York, NY, USA 10029
| | - Nicole R Kelly
- Department of Pediatrics, Division of Pediatric Genetic Medicine, Children’s Hospital at Montefiore/Montefiore Medical Center/Albert Einstein College of Medicine, Bronx, NY, USA 10467
| | - Whitley V Kelley
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA 35806
| | - Anna CE Hurst
- University of Alabama in Birmingham, Birmingham, AL, USA 35294
| | | | | | - Laura G Hendon
- University of Mississippi Medical Center, Jackson, MS, 39216
| | - E Martina Bebin
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA 35294
| | - Eimear E Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai. New York, NY, USA 10029
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA 10029
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA 10029
| | - Gregory M Cooper
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA 35806
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6
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Mighton C, Shickh S, Aguda V, Krishnapillai S, Adi-Wauran E, Bombard Y. From the patient to the population: Use of genomics for population screening. Front Genet 2022; 13:893832. [PMID: 36353115 PMCID: PMC9637971 DOI: 10.3389/fgene.2022.893832] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 09/26/2022] [Indexed: 10/22/2023] Open
Abstract
Genomic medicine is expanding from a focus on diagnosis at the patient level to prevention at the population level given the ongoing under-ascertainment of high-risk and actionable genetic conditions using current strategies, particularly hereditary breast and ovarian cancer (HBOC), Lynch Syndrome (LS) and familial hypercholesterolemia (FH). The availability of large-scale next-generation sequencing strategies and preventive options for these conditions makes it increasingly feasible to screen pre-symptomatic individuals through public health-based approaches, rather than restricting testing to high-risk groups. This raises anew, and with urgency, questions about the limits of screening as well as the moral authority and capacity to screen for genetic conditions at a population level. We aimed to answer some of these critical questions by using the WHO Wilson and Jungner criteria to guide a synthesis of current evidence on population genomic screening for HBOC, LS, and FH.
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Affiliation(s)
- Chloe Mighton
- Genomics Health Services Research Program, St. Michael’s Hospital, Unity Health Toronto, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Salma Shickh
- Genomics Health Services Research Program, St. Michael’s Hospital, Unity Health Toronto, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Vernie Aguda
- Genomics Health Services Research Program, St. Michael’s Hospital, Unity Health Toronto, Toronto, ON, Canada
- Centre for Medical Education, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Suvetha Krishnapillai
- Genomics Health Services Research Program, St. Michael’s Hospital, Unity Health Toronto, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Ella Adi-Wauran
- Genomics Health Services Research Program, St. Michael’s Hospital, Unity Health Toronto, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Yvonne Bombard
- Genomics Health Services Research Program, St. Michael’s Hospital, Unity Health Toronto, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
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7
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Hao L, Kraft P, Berriz GF, Hynes ED, Koch C, Korategere V Kumar P, Parpattedar SS, Steeves M, Yu W, Antwi AA, Brunette CA, Danowski M, Gala MK, Green RC, Jones NE, Lewis ACF, Lubitz SA, Natarajan P, Vassy JL, Lebo MS. Development of a clinical polygenic risk score assay and reporting workflow. Nat Med 2022; 28:1006-1013. [PMID: 35437332 PMCID: PMC9117136 DOI: 10.1038/s41591-022-01767-6] [Citation(s) in RCA: 96] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 03/02/2022] [Indexed: 12/31/2022]
Abstract
Implementation of polygenic risk scores (PRS) may improve disease prevention and management but poses several challenges: the construction of clinically valid assays, interpretation for individual patients, and the development of clinical workflows and resources to support their use in patient care. For the ongoing Veterans Affairs Genomic Medicine at Veterans Affairs (GenoVA) Study we developed a clinical genotype array-based assay for six published PRS. We used data from 36,423 Mass General Brigham Biobank participants and adjustment for population structure to replicate known PRS-disease associations and published PRS thresholds for a disease odds ratio (OR) of 2 (ranging from 1.75 (95% CI: 1.57-1.95) for type 2 diabetes to 2.38 (95% CI: 2.07-2.73) for breast cancer). After confirming the high performance and robustness of the pipeline for use as a clinical assay for individual patients, we analyzed the first 227 prospective samples from the GenoVA Study and found that the frequency of PRS corresponding to published OR > 2 ranged from 13/227 (5.7%) for colorectal cancer to 23/150 (15.3%) for prostate cancer. In addition to the PRS laboratory report, we developed physician- and patient-oriented informational materials to support decision-making about PRS results. Our work illustrates the generalizable development of a clinical PRS assay for multiple conditions and the technical, reporting and clinical workflow challenges for implementing PRS information in the clinic.
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Affiliation(s)
- Limin Hao
- Laboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA, USA
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Gabriel F Berriz
- Laboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA, USA
| | - Elizabeth D Hynes
- Laboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA, USA
| | - Christopher Koch
- Laboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA, USA
| | | | - Shruti S Parpattedar
- Laboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA, USA
| | - Marcie Steeves
- Laboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA, USA
- Medical Genetics, Massachusetts General Hospital, Boston, MA, USA
| | - Wanfeng Yu
- Laboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA, USA
| | - Ashley A Antwi
- Veterans Affairs Boston Healthcare System, Boston, MA, USA
| | | | | | - Manish K Gala
- Division of Gastroenterology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Robert C Green
- Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Precision Population Health, Ariadne Labs, Boston, MA, USA
| | - Natalie E Jones
- Veterans Affairs Boston Healthcare System, Boston, MA, USA
- Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Anna C F Lewis
- E J Safra Center for Ethics, Harvard University, Cambridge, MA, USA
| | - Steven A Lubitz
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, MA, USA
| | - Pradeep Natarajan
- Harvard Medical School, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Jason L Vassy
- Veterans Affairs Boston Healthcare System, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
- Precision Population Health, Ariadne Labs, Boston, MA, USA.
| | - Matthew S Lebo
- Laboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
- Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA
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8
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Cherukuri PF, Soe MM, Condon DE, Bartaria S, Meis K, Gu S, Frost FG, Fricke LM, Lubieniecki KP, Lubieniecka JM, Pyatt RE, Hajek C, Boerkoel CF, Carmichael L. Establishing analytical validity of BeadChip array genotype data by comparison to whole-genome sequence and standard benchmark datasets. BMC Med Genomics 2022; 15:56. [PMID: 35287663 PMCID: PMC8919546 DOI: 10.1186/s12920-022-01199-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Accepted: 02/28/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Clinical use of genotype data requires high positive predictive value (PPV) and thorough understanding of the genotyping platform characteristics. BeadChip arrays, such as the Global Screening Array (GSA), potentially offer a high-throughput, low-cost clinical screen for known variants. We hypothesize that quality assessment and comparison to whole-genome sequence and benchmark data establish the analytical validity of GSA genotyping. METHODS To test this hypothesis, we selected 263 samples from Coriell, generated GSA genotypes in triplicate, generated whole genome sequence (rWGS) genotypes, assessed the quality of each set of genotypes, and compared each set of genotypes to each other and to the 1000 Genomes Phase 3 (1KG) genotypes, a performance benchmark. For 59 genes (MAP59), we also performed theoretical and empirical evaluation of variants deemed medically actionable predispositions. RESULTS Quality analyses detected sample contamination and increased assay failure along the chip margins. Comparison to benchmark data demonstrated that > 82% of the GSA assays had a PPV of 1. GSA assays targeting transitions, genomic regions of high complexity, and common variants performed better than those targeting transversions, regions of low complexity, and rare variants. Comparison of GSA data to rWGS and 1KG data showed > 99% performance across all measured parameters. Consistent with predictions from prior studies, the GSA detection of variation within the MAP59 genes was 3/261. CONCLUSION We establish the analytical validity of GSA assays using quality analytics and comparison to benchmark and rWGS data. GSA assays meet the standards of a clinical screen although assays interrogating rare variants, transversions, and variants within low-complexity regions require careful evaluation.
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Affiliation(s)
- Praveen F Cherukuri
- Imagenetics, Sanford Health, 1410 W 25th St. Room #302, Sioux Falls, SD, 57105, USA. .,Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, USA. .,Sanford Research Center, Sioux Falls, SD, USA.
| | - Melissa M Soe
- Imagenetics, Sanford Health, 1410 W 25th St. Room #302, Sioux Falls, SD, 57105, USA
| | - David E Condon
- Imagenetics, Sanford Health, 1410 W 25th St. Room #302, Sioux Falls, SD, 57105, USA.,Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, USA
| | - Shubhi Bartaria
- Imagenetics, Sanford Health, 1410 W 25th St. Room #302, Sioux Falls, SD, 57105, USA
| | - Kaitlynn Meis
- Imagenetics, Sanford Health, 1410 W 25th St. Room #302, Sioux Falls, SD, 57105, USA
| | - Shaopeng Gu
- Imagenetics, Sanford Health, 1410 W 25th St. Room #302, Sioux Falls, SD, 57105, USA
| | - Frederick G Frost
- Imagenetics, Sanford Health, 1410 W 25th St. Room #302, Sioux Falls, SD, 57105, USA
| | - Lindsay M Fricke
- Imagenetics, Sanford Health, 1410 W 25th St. Room #302, Sioux Falls, SD, 57105, USA
| | - Krzysztof P Lubieniecki
- Imagenetics, Sanford Health, 1410 W 25th St. Room #302, Sioux Falls, SD, 57105, USA.,Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, USA.,Sanford Research Center, Sioux Falls, SD, USA
| | - Joanna M Lubieniecka
- Imagenetics, Sanford Health, 1410 W 25th St. Room #302, Sioux Falls, SD, 57105, USA.,Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, USA.,Sanford Research Center, Sioux Falls, SD, USA
| | - Robert E Pyatt
- Imagenetics, Sanford Health, 1410 W 25th St. Room #302, Sioux Falls, SD, 57105, USA.,Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, USA
| | - Catherine Hajek
- Imagenetics, Sanford Health, 1410 W 25th St. Room #302, Sioux Falls, SD, 57105, USA.,Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, USA
| | - Cornelius F Boerkoel
- Imagenetics, Sanford Health, 1410 W 25th St. Room #302, Sioux Falls, SD, 57105, USA
| | - Lynn Carmichael
- Imagenetics, Sanford Health, 1410 W 25th St. Room #302, Sioux Falls, SD, 57105, USA
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9
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Abstract
Applications of genomics to population screening are expanding in the United States and internationally. Many of these programs are being implemented in the context of healthcare systems, mostly in a clinical research setting, but there are some emerging examples of clinical models. This review examines these genomic population screening programs to identify common features and differences in screened conditions, genomic technology employed, approach to results disclosure, health outcomes, financial models, and sustainability. The diversity of approaches provides opportunities to learn and better understand the optimal approach to implementation based on the contextual setting. Expected final online publication date for the Annual Review of Genomics and Human Genetics, Volume 23 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Marc S Williams
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania, USA;
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10
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Blout Zawatsky CL, Shah N, Machini K, Perez E, Christensen KD, Zouk H, Steeves M, Koch C, Uveges M, Shea J, Gold N, Krier J, Boutin N, Mahanta L, Rehm HL, Weiss ST, Karlson EW, Smoller JW, Lebo MS, Green RC. Returning actionable genomic results in a research biobank: Analytic validity, clinical implementation, and resource utilization. Am J Hum Genet 2021; 108:2224-2237. [PMID: 34752750 PMCID: PMC8715145 DOI: 10.1016/j.ajhg.2021.10.005] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 10/15/2021] [Indexed: 12/14/2022] Open
Abstract
Over 100 million research participants around the world have had research array-based genotyping (GT) or genome sequencing (GS), but only a small fraction of these have been offered return of actionable genomic findings (gRoR). Between 2017 and 2021, we analyzed genomic results from 36,417 participants in the Mass General Brigham Biobank and offered to confirm and return pathogenic and likely pathogenic variants (PLPVs) in 59 genes. Variant verification prior to participant recontact revealed that GT falsely identified PLPVs in 44.9% of samples, and GT failed to identify 72.0% of PLPVs detected in a subset of samples that were also sequenced. GT and GS detected verified PLPVs in 1% and 2.5% of the cohort, respectively. Of 256 participants who were alerted that they carried actionable PLPVs, 37.5% actively or passively declined further disclosure. 76.3% of those carrying PLPVs were unaware that they were carrying the variant, and over half of those met published professional criteria for genetic testing but had never been tested. This gRoR protocol cost approximately $129,000 USD per year in laboratory testing and research staff support, representing $14 per participant whose DNA was analyzed or $3,224 per participant in whom a PLPV was confirmed and disclosed. These data provide logistical details around gRoR that could help other investigators planning to return genomic results.
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Affiliation(s)
- Carrie L Blout Zawatsky
- Brigham and Women's Hospital, Boston, MA 02115, USA; Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Ariadne Labs, Boston, MA 02215, USA; The MGH Institute of Health Professions, Boston, MA 02129, USA
| | - Nidhi Shah
- Brigham and Women's Hospital, Boston, MA 02115, USA; Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Harvard Medical School, Boston, MA 02115, USA
| | - Kalotina Machini
- Harvard Medical School, Boston, MA 02115, USA; Laboratory for Molecular Medicine, Cambridge, MA 02139, USA
| | - Emma Perez
- Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Kurt D Christensen
- Harvard Medical School, Boston, MA 02115, USA; Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - Hana Zouk
- Harvard Medical School, Boston, MA 02115, USA; Laboratory for Molecular Medicine, Cambridge, MA 02139, USA
| | - Marcie Steeves
- Laboratory for Molecular Medicine, Cambridge, MA 02139, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | | | - Melissa Uveges
- Connell School of Nursing, Boston College, Chestnut Hill, MA 02467, USA
| | - Janelle Shea
- Division of Medical Genetics, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Nina Gold
- Harvard Medical School, Boston, MA 02115, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Mass General Brigham Personalized Medicine, Cambridge, MA 02139, USA
| | - Joel Krier
- Brigham and Women's Hospital, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA
| | - Natalie Boutin
- Mass General Brigham Personalized Medicine, Cambridge, MA 02139, USA
| | - Lisa Mahanta
- Laboratory for Molecular Medicine, Cambridge, MA 02139, USA; Mass General Brigham Personalized Medicine, Cambridge, MA 02139, USA
| | - Heidi L Rehm
- Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Harvard Medical School, Boston, MA 02115, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Mass General Brigham Personalized Medicine, Cambridge, MA 02139, USA
| | - Scott T Weiss
- Brigham and Women's Hospital, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA; Laboratory for Molecular Medicine, Cambridge, MA 02139, USA; Mass General Brigham Personalized Medicine, Cambridge, MA 02139, USA
| | - Elizabeth W Karlson
- Brigham and Women's Hospital, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA; Mass General Brigham Personalized Medicine, Cambridge, MA 02139, USA
| | - Jordan W Smoller
- Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Harvard Medical School, Boston, MA 02115, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Mass General Brigham Personalized Medicine, Cambridge, MA 02139, USA
| | - Matthew S Lebo
- Brigham and Women's Hospital, Boston, MA 02115, USA; Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Harvard Medical School, Boston, MA 02115, USA; Laboratory for Molecular Medicine, Cambridge, MA 02139, USA; Mass General Brigham Personalized Medicine, Cambridge, MA 02139, USA
| | - Robert C Green
- Brigham and Women's Hospital, Boston, MA 02115, USA; Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Ariadne Labs, Boston, MA 02215, USA; Harvard Medical School, Boston, MA 02115, USA; Mass General Brigham Personalized Medicine, Cambridge, MA 02139, USA.
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