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Choate LA, Koleilat A, Harris K, Vidal-Folch N, Guenzel A, Newman J, Peterson BJ, Peterson SE, Rice CS, Train LJ, Hasadsri L, Marcou CA, Moyer AM, Baudhuin LM. Confirmation of Insertion, Deletion, and Deletion-Insertion Variants Detected by Next-Generation Sequencing. Clin Chem 2023; 69:1155-1162. [PMID: 37566393 DOI: 10.1093/clinchem/hvad110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 07/03/2023] [Indexed: 08/12/2023]
Abstract
BACKGROUND Despite clinically demonstrated accuracy in next generation sequencing (NGS) data, many clinical laboratories continue to confirm variants with Sanger sequencing, which increases cost of testing and turnaround time. Several studies have assessed the accuracy of NGS in detecting single nucleotide variants; however, less has been reported about insertion, deletion, and deletion-insertion variants (indels). METHODS We performed a retrospective analysis from 2015-2022 of indel results from a subset of NGS targeted gene panel tests offered through the Mayo Clinic Genomics Laboratories. We compared results from NGS and Sanger sequencing of indels observed in clinical runs and during the intra-assay validation of the tests. RESULTS Results demonstrated 100% concordance between NGS and Sanger sequencing for over 490 indels (217 unique), ranging in size from 1 to 68 basepairs (bp). The majority of indels were deletions (77%) and 1 to 5 bp in length (90%). Variant frequencies ranged from 11.4% to 67.4% and 85.1% to 100% for heterozygous and homozygous variants, respectively, with a median depth of coverage of 2562×. A subset of indels (7%) were located in complex regions of the genome, and these were accurately detected by NGS. We also demonstrated 100% reproducibility of indel detection (n = 179) during intra-assay validation. CONCLUSIONS Together this data demonstrates that reportable indel variants up to 68 bp can be accurately assessed using NGS, even when they occur in complex regions. Depending on the complexity of the region or variant, Sanger sequence confirmation of indels is usually not necessary if the variants meet appropriate coverage and allele frequency thresholds.
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Affiliation(s)
- Lauren A Choate
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Alaa Koleilat
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Kimberley Harris
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Noemi Vidal-Folch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Adam Guenzel
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Jessica Newman
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Brenda J Peterson
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Sandra E Peterson
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Christopher S Rice
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Laura J Train
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Linda Hasadsri
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Cherisse A Marcou
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Ann M Moyer
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Linnea M Baudhuin
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
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Atiq MA, Peterson SE, Langman LJ, Baudhuin LM, Black JL, Moyer AM. Determination of the Duplicated CYP2D6 Allele Using Real-Time PCR Signal: An Alternative Approach. J Pers Med 2023; 13:883. [PMID: 37373874 DOI: 10.3390/jpm13060883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 05/17/2023] [Accepted: 05/20/2023] [Indexed: 06/29/2023] Open
Abstract
CYP2D6 duplication has important pharmacogenomic implications. Reflex testing with long-range PCR (LR-PCR) can resolve the genotype when a duplication and alleles with differing activity scores are detected. We evaluated whether visual inspection of plots from real-time-PCR-based targeted genotyping with copy number variation (CNV) detection could reliably determine the duplicated CYP2D6 allele. Six reviewers evaluated QuantStudio OpenArray CYP2D6 genotyping results and the TaqMan Genotyper plots for seventy-three well-characterized cases with three copies of CYP2D6 and two different alleles. Reviewers blinded to the final genotype visually assessed the plots to determine the duplicated allele or opt for reflex sequencing. Reviewers achieved 100% accuracy for cases with three CYP2D6 copies that they opted to report. Reviewers did not request reflex sequencing in 49-67 (67-92%) cases (and correctly identified the duplicated allele in each case); all remaining cases (6-24) were marked by at least one reviewer for reflex sequencing. In most cases with three copies of CYP2D6, the duplicated allele can be determined using a combination of targeted genotyping using real-time PCR with CNV detection without need for reflex sequencing. In ambiguous cases and those with >3 copies, LR-PCR and Sanger sequencing may still be necessary for determination of the duplicated allele.
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Affiliation(s)
- Mazen A Atiq
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 1st Street Southwest, Rochester, MN 55905, USA
| | - Sandra E Peterson
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 1st Street Southwest, Rochester, MN 55905, USA
| | - Loralie J Langman
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 1st Street Southwest, Rochester, MN 55905, USA
| | - Linnea M Baudhuin
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 1st Street Southwest, Rochester, MN 55905, USA
| | - John L Black
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 1st Street Southwest, Rochester, MN 55905, USA
| | - Ann M Moyer
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 1st Street Southwest, Rochester, MN 55905, USA
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3
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Wang L, Scherer SE, Bielinski SJ, Muzny DM, Jones LA, Black JL, Moyer AM, Giri J, Sharp RR, Matey ET, Wright JA, Oyen LJ, Nicholson WT, Wiepert M, Sullard T, Curry TB, Vitek CRR, McAllister TM, Sauver JL, Caraballo PJ, Lazaridis KN, Venner E, Qin X, Hu J, Kovar CL, Korchina V, Walker K, Doddapaneni H, Wu TJ, Raj R, Denson S, Liu W, Chandanavelli G, Zhang L, Wang Q, Kalra D, Karow MB, Harris KJ, Sicotte H, Peterson SE, Barthel AE, Moore BE, Skierka JM, Kluge ML, Kotzer KE, Kloke K, Vander Pol JM, Marker H, Sutton JA, Kekic A, Ebenhoh A, Bierle DM, Schuh MJ, Grilli C, Erickson S, Umbreit A, Ward L, Crosby S, Nelson EA, Levey S, Elliott M, Peters SG, Pereira N, Frye M, Shamoun F, Goetz MP, Kullo IJ, Wermers R, Anderson JA, Formea CM, El Melik RM, Zeuli JD, Herges JR, Krieger CA, Hoel RW, Taraba JL, Thomas SR, Absah I, Bernard ME, Fink SR, Gossard A, Grubbs PL, Jacobson TM, Takahashi P, Zehe SC, Buckles S, Bumgardner M, Gallagher C, Fee-Schroeder K, Nicholas NR, Powers ML, Ragab AK, Richardson DM, Stai A, Wilson J, Pacyna JE, Olson JE, Sutton EJ, Beck AT, Horrow C, Kalari KR, Larson NB, Liu H, Wang L, Lopes GS, Borah BJ, Freimuth RR, Zhu Y, Jacobson DJ, Hathcock MA, Armasu SM, McGree ME, Jiang R, Koep TH, Ross JL, Hilden M, Bosse K, Ramey B, Searcy I, Boerwinkle E, Gibbs RA, Weinshilboum RM. Implementation of preemptive DNA sequence-based pharmacogenomics testing across a large academic medical center: The Mayo-Baylor RIGHT 10K Study. Genet Med 2022; 24:1062-1072. [PMID: 35331649 PMCID: PMC9272414 DOI: 10.1016/j.gim.2022.01.022] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 01/25/2022] [Accepted: 01/26/2022] [Indexed: 12/12/2022] Open
Abstract
PURPOSE The Mayo-Baylor RIGHT 10K Study enabled preemptive, sequence-based pharmacogenomics (PGx)-driven drug prescribing practices in routine clinical care within a large cohort. We also generated the tools and resources necessary for clinical PGx implementation and identified challenges that need to be overcome. Furthermore, we measured the frequency of both common genetic variation for which clinical guidelines already exist and rare variation that could be detected by DNA sequencing, rather than genotyping. METHODS Targeted oligonucleotide-capture sequencing of 77 pharmacogenes was performed using DNA from 10,077 consented Mayo Clinic Biobank volunteers. The resulting predicted drug response-related phenotypes for 13 genes, including CYP2D6 and HLA, affecting 21 drug-gene pairs, were deposited preemptively in the Mayo electronic health record. RESULTS For the 13 pharmacogenes of interest, the genomes of 79% of participants carried clinically actionable variants in 3 or more genes, and DNA sequencing identified an average of 3.3 additional conservatively predicted deleterious variants that would not have been evident using genotyping. CONCLUSION Implementation of preemptive rather than reactive and sequence-based rather than genotype-based PGx prescribing revealed nearly universal patient applicability and required integrated institution-wide resources to fully realize individualized drug therapy and to show more efficient use of health care resources.
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Affiliation(s)
- Liewei Wang
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN,Division of Clinical Pharmacology, Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN
| | - Steven E. Scherer
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX
| | - Suzette J. Bielinski
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Donna M. Muzny
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Leila A. Jones
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | - John Logan Black
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Ann M. Moyer
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Jyothsna Giri
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | | | | | | | | | - Wayne T. Nicholson
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN
| | - Mathieu Wiepert
- Department of Information Technology, Mayo Clinic, Rochester, MN
| | - Terri Sullard
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | - Timothy B. Curry
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN,Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN
| | | | | | - Jennifer L. Sauver
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN,Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Pedro J. Caraballo
- Division of General Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Konstantinos N. Lazaridis
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN,Division of Gastroenterology and Hepatology, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Eric Venner
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Xiang Qin
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Jianhong Hu
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Christie L. Kovar
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Viktoriya Korchina
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Kimberly Walker
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | | | - Tsung-Jung Wu
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Ritika Raj
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Shawn Denson
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Wen Liu
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Gauthami Chandanavelli
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Lan Zhang
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Qiaoyan Wang
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Divya Kalra
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Mary Beth Karow
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | | | - Hugues Sicotte
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Sandra E. Peterson
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Amy E. Barthel
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Brenda E. Moore
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | | | - Michelle L. Kluge
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Katrina E. Kotzer
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Karen Kloke
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | | | - Heather Marker
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | - Joseph A. Sutton
- Department of Information Technology, Mayo Clinic, Rochester, MN
| | | | | | - Dennis M. Bierle
- Division of General Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | | | | | | | - Audrey Umbreit
- Department of Pharmacy, Mayo Clinic Health System, Mankato, MN
| | - Leah Ward
- Department of Pharmacy, Mayo Clinic, Jacksonville, FL
| | - Sheena Crosby
- Department of Pharmacy, Mayo Clinic, Jacksonville, FL
| | | | - Sharon Levey
- Department of Clinical Genomics, Mayo Clinic, Scottsdale, AZ
| | - Michelle Elliott
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Steve G. Peters
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Naveen Pereira
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | - Mark Frye
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN
| | - Fadi Shamoun
- Department of Cardiovascular Medicine Mayo Clinic, Phoenix, AZ
| | - Matthew P. Goetz
- Division of Medical Oncology, Department of Oncology, Mayo Clinic, Rochester, MN
| | | | - Robert Wermers
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | | | | | | | | | | | | | | | | | - Scott R. Thomas
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | - Imad Absah
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | | | - Stephanie R. Fink
- Division of Community Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Andrea Gossard
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | | | | | - Paul Takahashi
- Division of Community Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | | | - Susan Buckles
- Department of Public Affairs, Mayo Clinic, Rochester, MN
| | | | | | | | | | - Melody L. Powers
- Biospecimens Accessioning and Processing Laboratory, Mayo Clinic, Rochester, MN
| | - Ahmed K. Ragab
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | | | - Anthony Stai
- Department of Information Technology, Mayo Clinic, Rochester, MN
| | - Jaymi Wilson
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | - Joel E. Pacyna
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN
| | - Janet E. Olson
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN,Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN
| | - Erica J. Sutton
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN
| | - Annika T. Beck
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN
| | - Caroline Horrow
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN
| | - Krishna R. Kalari
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Nicholas B. Larson
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Hongfang Liu
- Division of Digital Health Sciences, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Liwei Wang
- Division of Digital Health Sciences, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Guilherme S. Lopes
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN,Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Bijan J. Borah
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN,Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Robert R. Freimuth
- Division of Digital Health Sciences, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Ye Zhu
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Debra J. Jacobson
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Matthew A. Hathcock
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Sebastian M. Armasu
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Michaela E. McGree
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Ruoxiang Jiang
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | | | | | | | | | | | | | - Eric Boerwinkle
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX,Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX,School of Public Health, University of Texas Health Science Center at Houston, Houston, TX
| | - Richard A. Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX,Corresponding Authors (), ()
| | - Richard M. Weinshilboum
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN,Division of Clinical Pharmacology, Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN,Corresponding Authors (), ()
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4
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Lopes JL, Harris K, Karow MB, Peterson SE, Kluge ML, Kotzer KE, Lopes GS, Larson NB, Bielinski SJ, Scherer SE, Wang L, Weinshilboum RM, Black JL, Moyer AM. Targeted Genotyping in Clinical Pharmacogenomics: What Is Missing? J Mol Diagn 2022; 24:253-261. [PMID: 35041929 PMCID: PMC8961466 DOI: 10.1016/j.jmoldx.2021.11.008] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 11/09/2021] [Accepted: 11/29/2021] [Indexed: 01/01/2023] Open
Abstract
Clinical pharmacogenomic testing typically uses targeted genotyping, which only detects variants included in the test design and may vary among laboratories. To evaluate the potential patient impact of genotyping compared with sequencing, which can detect common and rare variants, an in silico targeted genotyping panel was developed based on the variants most commonly included in clinical tests and applied to a cohort of 10,030 participants who underwent sequencing for CYP1A2, CYP2C19, CYP2C9, CYP2D6, CYP3A4, CYP3A5, DPYD, SLCO1B1, TPMT, UGT1A1, and VKORC1. The results of in silico targeted genotyping were compared with the clinically reported sequencing results. Of the 10,030 participants, 2780 (28%) had at least one potentially clinically relevant variant/allele identified by sequencing that would not have been detected in a standard targeted genotyping panel. The genes with the largest number of participants with variants only detected by sequencing were SLCO1B1, DPYD, and CYP2D6, which affected 13%, 6.3%, and 3.5% of participants, respectively. DPYD (112 variants) and CYP2D6 (103 variants) had the largest number of unique variants detected only by sequencing. Although targeted genotyping detects most clinically significant pharmacogenomic variants, sequencing-based approaches are necessary to detect rare variants that collectively affect many patients. However, efforts to establish pharmacogenomic variant classification systems and nomenclature to accommodate rare variants will be required to adopt sequencing-based pharmacogenomics.
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Affiliation(s)
- Jaime L. Lopes
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Kimberley Harris
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Mary Beth Karow
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Sandra E. Peterson
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Michelle L. Kluge
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Katrina E. Kotzer
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Guilherme S. Lopes
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | - Nicholas B. Larson
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | | | - Steven E. Scherer
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas
| | - Liewei Wang
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, Minnesota
| | - Richard M. Weinshilboum
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, Minnesota
| | - John L. Black
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Ann M. Moyer
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota,Address correspondence to Ann M. Moyer, M.D., Ph.D., Mayo Clinic, 200 First St SW, Rochester, MN 55905.
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5
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Haberkorn SM, Bueter SI, Kelm M, Hopkin G, Peterson SE. 392Systematic review and meta-analysis on the diagnostic accuracy for the detection of relevant coronary artery stenosis of vasodilator myocardial perfusion CMR and dobutamine stress echocardiography. Eur Heart J 2019. [DOI: 10.1093/eurheartj/ehz747.0098] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Background
Relevance of coronary artery stenosis in patients with stabile coronary artery disease (SCAD) is defined by myocardial ischemia due to flow limitation. While FFR-guided treatment of SCAD is a class IA recommendation. The initial risk stratification with detection of relevant CAD can be facilitated by several myocardial imaging methods without any preference mentioned in current guidelines.
Objectives
This study aimed to systematically assess and to compare the diagnostic accuracy of vasodilator myocardial perfusion cardiovascular magnetic resonance imaging (pCMR) and dobutamine stress echocardiography (DSE) for the non-invasive detection of relevant SCAD through a meta-analysis, to enable an evidential preference in risk stratification. In contrast to previously published work, this meta-analysis explicitly included only studies with rigorous eligibility criteria and a narrowly prespecified definition of their invasive reference tests.
Selection criteria
A study was included if (1) CCA or FFR was used as a reference standard for diagnosing relevant SCAD, defined as >70% stenosis or a value <0.80 on FFR recordings, respectively; (2) sufficient data to permit analysis and to reconstruct contingency tables (explicitly true-positive, false-positive, false-negative and true-negative findings) was provided; (3) there was a minimal sample size of 20 patients; (4) assessment of myocardial perfusion reserve was performed using vasodilators adenosine or regadenoson for pCMR, and dobutamine used for echocardiography; and (5) the studies were of prospective design.
Data collection and analysis: From the 5,634 studies identified, 1,306 relevant articles were selected after title screening. Just 47 fulfilled all inclusion criteria on full-text review, resulting in a total sample size of 4,742 patients. Data extraction was performed for each study by two reviewers independently.Pooled analysis was performed based on a random effects models.
Results
The sensitivity, specificity and diagnostic odds ratio (DOR) for pCMR were 0.88 (95% confidence interval (CI): 0.85–0.90), 0.84 (95% CI: 0.81–0.87), and 38 (95% CI: 29–49), and for DSE 0.72 (95% CI: 0.61–0.81), 0.89 (95% CI: 0.83–0.93), and 20 (95% CI: 9–46), respectively. Post-test probability was augmented by positive (likelihood ratio) LR of 5.5 (95% CI: 4.7–6.5) and negative LR of 0.14 (95% CI: 0.12–0.18) based on Bayes' theorem, as compared to LR of 6.3 (95% CI: 3.8, 10.4) and negative LR of 0.31 (95% CI: 0.21, 0.46) for DSE. The size of the prediction region on the hierarchical summary receiver operating characteristic (HSROC) plot for pCMR (0.29; 95% CI 0.11–0.77) was significantly smaller compared to the one of DSE (1.07; 95% CI 0.27–4.19; p<0.01).
Forrest plot pCMR
Conclusion
The results of this systematic review and meta-analysis show that pCMR is characterized by a superior diagnostic test accuracy of relevant SCAD compared to DSE and that it can refine the post-test probability of SCAD.
Acknowledgement/Funding
European Heart Academy of the European Society of Cardiology
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Affiliation(s)
- S M Haberkorn
- Universityhospital Duesseldorf, Cardiology, Pneumology and Angiology, Duesseldorf, Germany
| | - S I Bueter
- Universityhospital Duesseldorf, Cardiology, Pneumology and Angiology, Duesseldorf, Germany
| | - M Kelm
- Universityhospital Duesseldorf, Cardiology, Pneumology and Angiology, Duesseldorf, Germany
| | - G Hopkin
- London School of Economics and Political Science, Health Politics, London, United Kingdom
| | - S E Peterson
- Barts Health NHS Trust, Barts Heart Centre, St Bartholomew's Hospital, London, United Kingdom
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6
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V Willrich MA, Kaleta EJ, Bryant SC, Spears GM, Train LJ, Peterson SE, Lennon VA, Kopecky SL, Baudhuin LM. Genetic variation in statin intolerance and a possible protective role for UGT1A1. Pharmacogenomics 2017; 19:83-94. [PMID: 29210320 DOI: 10.2217/pgs-2017-0146] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
The etiology of statin intolerance is hypothesized to be due to genetic variants that impact statin disposition and clearance. We sought to determine whether genetic variants were associated to statin intolerance. The studied cohort consisted of hyperlipidemic participants (n = 90) clinically diagnosed with statin intolerance by a cardiologist and matched controls without statin intolerance. Creatine kinase activity, lipid profiles and genetic analyses were performed on genes involved in statin metabolism and included UGT1A1 and UGT1A3 sequencing and targeted analyses of CYP3A4*22, CYP3A5*3, SLCO1B1*5 and *1b, ABCB1 c.3435C>T, ABCG2 c.421C>A and GATM rs9806699. Although lipids were higher in cases, genetic variant minor allele frequencies were similar between cases and controls, except for UGT1A1*28, which was less prevalent in cases than controls.
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Affiliation(s)
| | - Erin J Kaleta
- Department of Laboratory Medicine & Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | - Sandra C Bryant
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Grant M Spears
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Laura J Train
- Department of Laboratory Medicine & Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | - Sandra E Peterson
- Department of Laboratory Medicine & Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | - Vanda A Lennon
- Department of Laboratory Medicine & Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | - Stephen L Kopecky
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN 55905, USA
| | - Linnea M Baudhuin
- Department of Laboratory Medicine & Pathology, Mayo Clinic, Rochester, MN 55905, USA
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Ji Y, Skierka JM, Blommel JH, Moore BE, VanCuyk DL, Bruflat JK, Peterson LM, Veldhuizen TL, Fadra N, Peterson SE, Lagerstedt SA, Train LJ, Baudhuin LM, Klee EW, Ferber MJ, Bielinski SJ, Caraballo PJ, Weinshilboum RM, Black JL. Preemptive Pharmacogenomic Testing for Precision Medicine: A Comprehensive Analysis of Five Actionable Pharmacogenomic Genes Using Next-Generation DNA Sequencing and a Customized CYP2D6 Genotyping Cascade. J Mol Diagn 2016; 18:438-445. [PMID: 26947514 DOI: 10.1016/j.jmoldx.2016.01.003] [Citation(s) in RCA: 138] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2015] [Revised: 12/24/2015] [Accepted: 01/11/2016] [Indexed: 01/08/2023] Open
Abstract
Significant barriers, such as lack of professional guidelines, specialized training for interpretation of pharmacogenomics (PGx) data, and insufficient evidence to support clinical utility, prevent preemptive PGx testing from being widely clinically implemented. The current study, as a pilot project for the Right Drug, Right Dose, Right Time-Using Genomic Data to Individualize Treatment Protocol, was designed to evaluate the impact of preemptive PGx and to optimize the workflow in the clinic setting. We used an 84-gene next-generation sequencing panel that included SLCO1B1, CYP2C19, CYP2C9, and VKORC1 together with a custom-designed CYP2D6 testing cascade to genotype the 1013 subjects in laboratories approved by the Clinical Laboratory Improvement Act. Actionable PGx variants were placed in patient's electronic medical records where integrated clinical decision support rules alert providers when a relevant medication is ordered. The fraction of this cohort carrying actionable PGx variant(s) in individual genes ranged from 30% (SLCO1B1) to 79% (CYP2D6). When considering all five genes together, 99% of the subjects carried an actionable PGx variant(s) in at least one gene. Our study provides evidence in favor of preemptive PGx testing by identifying the risk of a variant being present in the population we studied.
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Affiliation(s)
- Yuan Ji
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Jennifer M Skierka
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Joseph H Blommel
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Brenda E Moore
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Douglas L VanCuyk
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Jamie K Bruflat
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Lisa M Peterson
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | | | - Numrah Fadra
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Sandra E Peterson
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Susan A Lagerstedt
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Laura J Train
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Linnea M Baudhuin
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Eric W Klee
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota; Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota
| | - Matthew J Ferber
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota; Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota
| | | | - Pedro J Caraballo
- Department of General Internal Medicine, Mayo Clinic, Rochester, Minnesota
| | - Richard M Weinshilboum
- Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota; Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, Minnesota
| | - John L Black
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota.
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Peterson SE, Nelson JL, Guthrie KA, Gadi VK, Aydelotte TM, Oyer DJ, Prager SW, Gammill HS. Prospective assessment of fetal-maternal cell transfer in miscarriage and pregnancy termination. Hum Reprod 2012; 27:2607-12. [PMID: 22752611 DOI: 10.1093/humrep/des244] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND Fetal cells (microchimerism) are acquired by women during pregnancy. Fetal microchimerism persists decades later and includes cells with pluripotent capacity. Persistent microchimerism has the capacity for both beneficial and detrimental maternal health consequences. Both miscarriage and termination of pregnancy can result in fetal microchimerism. We sought to determine whether cellular fetal microchimerism is acquired during management of pregnancy loss and further explored factors that could influence fetal cell transfer, including viability of fetal tissue, surgical versus medical management and gestational age. METHODS Pregnant women (n= 150 samples from 75 women) with singleton pregnancies undergoing a TOP (n= 63) or treatment for embryonic or fetal demise (miscarriage, n= 12) were enrolled. Mononuclear cells were isolated from blood samples drawn before, and 30 min after, treatment. Fetal cellular microchimerism concentrations were determined using quantitative PCR for a Y chromosome-specific sequence, expressed as genome equivalents of fetal DNA per 100 000 maternal cell equivalents (gEq/10(5)). Detection rate ratios were determined according to clinical characteristics. RESULTS Cellular fetal microchimerism was found more often in post- compared with pretreatment samples, 24 versus 5% (P= 0.004) and at higher concentrations, 0-36 versus 0-0.7 gEq/10(5) (P< 0.001). Likelihood of microchimerism was higher in surgical than medical management, detection rate ratio 24.7 (P= 0.02). The detection rate ratio for TOP versus miscarriage was 16.7 for known male fetuses (P= 0.02). Microchimerism did not vary with gestational age. CONCLUSIONS Significant fetal cell transfer occurs during miscarriage and TOP. Exploratory analyses support relationships between obstetric clinical factors and acquisition of fetal cellular microchimerism; however, our limited sample size precludes definitive analysis of these relationships, and confirmation is needed. In addition, the long-term persistence and potential consequences of fetal microchimerism on maternal health merit further investigation.
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Affiliation(s)
- S E Peterson
- Department of Obstetrics & Gynecology, University of Washington, Box 356460, Seattle, WA 98195-6460, USA
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9
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Skierka JM, Walker DL, Peterson SE, O’Kane DJ, Black JL. CYP2D6*11 and challenges in clinical genotyping of the highly polymorphic CYP2D6 gene. Pharmacogenomics 2012; 13:951-4. [DOI: 10.2217/pgs.12.56] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
CYP2D6 is genotyped clinically for prediction of response to tamoxifen, psychotropic drugs and other medications. Phenotype prediction is dependent upon accurate genotyping. The CYP Allele Nomenclature Committee maintains the allelic nomenclature for CYP2D6; however, in some cases, the list of polymorphisms associated with a given allele is incomplete. Clinical laboratories and in vitro diagnostic manufacturers rely upon this nomenclature, in addition to the literature, to infer allelic function and haplotypes and when they design CYP2D6-testing platforms. This article provides more complete sequencing data for the CYP2D6*11 allele and describes the difficulties encountered in genotyping CYP2D6 when incomplete data are available. The CYP Allele Nomenclature Committee should provide clear information about the completeness of the original data used to define each allele.
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Affiliation(s)
- Jennifer M Skierka
- Nucleotide Polymorphism Laboratory, Department of Laboratory Medicine & Pathology, Mayo Clinic, 200 1st Street SW, Rochester, MN 55902, USA
| | - Denise L Walker
- Functional Neurogenomics Laboratory, Department of Psychiatry & Psychology, Mayo Clinic & Mayo Medical School, Rochester, MN 55902, USA
| | - Sandra E Peterson
- Nucleotide Polymorphism Laboratory, Department of Laboratory Medicine & Pathology, Mayo Clinic, 200 1st Street SW, Rochester, MN 55902, USA
| | - Dennis J O’Kane
- Nucleotide Polymorphism Laboratory, Department of Laboratory Medicine & Pathology, Mayo Clinic, 200 1st Street SW, Rochester, MN 55902, USA
| | - John Logan Black
- Nucleotide Polymorphism Laboratory, Department of Laboratory Medicine & Pathology, Mayo Clinic, 200 1st Street SW, Rochester, MN 55902, USA
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Abstract
The brain is remarkable for its complex organization and functions, which have been historically assumed to arise from cells with identical genomes. However, recent studies have shown that the brain is in fact a complex genetic mosaic of aneuploid and euploid cells. The precise function of neural aneuploidy and mosaicism are currently being examined on multiple fronts that include contributions to cellular diversity, cellular signaling and diseases of the central nervous system (CNS). Constitutive aneuploidy in genetic diseases has proven roles in brain dysfunction, as observed in Down syndrome (trisomy 21) and mosaic variegated aneuploidy. The existence of aneuploid cells within normal individuals raises the possibility that these cells might have distinct functions in the normal and diseased brain, the latter contributing to sporadic CNS disorders including cancer. Here we review what is known about neural aneuploidy, and offer speculations on its role in diseases of the brain.
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Affiliation(s)
- M A Kingsbury
- Department of Molecular Biology, Helen L. Dorris Institute for the Study of Neurological and Psychiatric Disorders of Children and Adolescents, The Scripps Research Institute, La Jolla, California 92037, USA.
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11
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Peterson SE, Stellwagen AE, Diede SJ, Singer MS, Haimberger ZW, Johnson CO, Tzoneva M, Gottschling DE. The function of a stem-loop in telomerase RNA is linked to the DNA repair protein Ku. Nat Genet 2001; 27:64-7. [PMID: 11138000 DOI: 10.1038/83778] [Citation(s) in RCA: 173] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
The telomerase enzyme lengthens telomeres, an activity essential for chromosome stability in most eukaryotes. The enzyme is composed of a specialized reverse transcriptase and a template RNA. In Saccharomyces cerevisiae, overexpression of TLC1, the telomerase RNA gene, disrupts telomeric structure. The result is both shortened telomere length and loss of a special chromatin structure that normally silences telomere-proximal genes. Because telomerase function is not required for telomeric silencing, we postulated that the dominant-negative effect caused by overexpression of TLC1 RNA originates in a normal interaction between the RNA and an unknown telomeric factor important for silencing; the overexpressed RNA presumably continues to bind the factor and compromises its function. Here we show that a 48-nt stem-loop structure within the 1.3-kb TLC1 RNA is necessary and sufficient for disrupting telomeric silencing and shortening telomeres. Moreover, this short RNA sequence appears to function through an interaction with the conserved DNA end-binding protein Ku. We propose that, in addition to its roles in telomeric silencing, homologous recombination and non-homologous end-joining (NHEJ), S. cerevisiae Ku also helps to recruit or activate telomerase at the telomere through an interaction with this stem-loop of TLC1 RNA.
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Affiliation(s)
- S E Peterson
- Division of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
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Abstract
Hürthle cell adenomas (HCAs) are a rare and potentially lethal variant of follicular tumors of the thyroid. Considerable controversy exists regarding potential risk factors, diagnosis, and treatment of HCAs. The authors report the case of a 38-year-old male patient with an 8.3 cm x 3.5 cm HCA. Diagnosis was made preoperatively from a core needle biopsy and confirmed postoperatively on frozen section. Treatment consisted of a right lobectomy.
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Affiliation(s)
- A Desai
- University of Health Sciences, Kansas City, Mo., USA
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13
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Singer MS, Kahana A, Wolf AJ, Meisinger LL, Peterson SE, Goggin C, Mahowald M, Gottschling DE. Identification of high-copy disruptors of telomeric silencing in Saccharomyces cerevisiae. Genetics 1998; 150:613-32. [PMID: 9755194 PMCID: PMC1460361 DOI: 10.1093/genetics/150.2.613] [Citation(s) in RCA: 367] [Impact Index Per Article: 14.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The ends of chromosomes in Saccharomyces cerevisiae initiate a repressive chromatin structure that spreads internally and inhibits the transcription of nearby genes, a phenomenon termed telomeric silencing. To investigate the molecular basis of this process, we carried out a genetic screen to identify genes whose overexpression disrupts telomeric silencing. We thus isolated 10 DOT genes (disruptor of telomeric silencing). Among these were genes encoding chromatin component Sir4p, DNA helicase Dna2p, ribosomal protein L32, and two proteins of unknown function, Asf1p and Ifh1p. The collection also included genes that had not previously been identified: DOT1, DOT4, DOT5, DOT6, and TLC1, which encodes the RNA template component of telomerase. With the exception of TLC1, all these genes, particularly DOT1 and DOT4, also reduced silencing at other repressed loci (HM loci and rDNA) when overexpressed. Moreover, deletion of the latter two genes weakened silencing as well, suggesting that DOT1 and DOT4 normally play important roles in gene repression. DOT1 deletion also affected telomere tract length. The function of Dot1p is not known. The sequence of Dot4p suggests that it is a ubiquitin-processing protease. Taken together, the DOT genes include both components and regulators of silent chromatin.
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Affiliation(s)
- M S Singer
- Department of Molecular Genetics and Cell Biology, The University of Chicago, Chicago, Illinois 60637, USA
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14
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Bernstein GA, Peterson SE, Perwien AR, Borchardt CM, Kushner MG. Management of blood-drawing fears in adolescents with comorbid anxiety and depressive disorders. J Child Adolesc Psychopharmacol 1996; 6:53-61. [PMID: 9231299 DOI: 10.1089/cap.1996.6.53] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
As more pharmacologic treatment and research on child and adolescent psychiatric patients are conducted, the common problem of blood-drawing fears will need to be addressed. Avoidance of blood-drawing could jeopardize an individual's physical and mental health, and inhibit the collection of data aimed at furthering the study of psychiatric disorders in youth. This report describes the naturalistic application of specific techniques for managing severe blood-drawing fears in adolescent subjects undergoing a clinical trial. The adolescents (ages 12-18) were 44 consecutive school refusers with comorbid anxiety and major depressive disorders. Of the school-refusing adolescents, 27% (12 of 44) were observed to have a severe fear of blood-drawing. A management strategy comprised of providing information, distraction, supportive reassurance, and exposure appeared successful in managing the fears of blood-drawing in all of the adolescents, except two. These 2 adolescents refused to enter the treatment study due to a marked fear of blood-drawing. All 10 subjects who exhibited a fear of blood-drawing and were able to complete the initial blood test, using the interventions noted, were able to obtain subsequent venipunctures with minimal or no avoidance behavior. These preliminary findings suggest that blood-drawing fears can be effectively managed in most cases, though controlled studies of these interventions are needed.
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Affiliation(s)
- G A Bernstein
- Division of Child and Adolescent Psychiatry, University of Minnesota Medical School, Minneapolis 55455, USA
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15
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Peterson SE, Peterson MD, Raymond G, Gilligan C, Checovich MM, Smith EL. Muscular strength and bone density with weight training in middle-aged women. Med Sci Sports Exerc 1991; 23:499-504. [PMID: 2056907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Previous research has demonstrated positive correlations between bone mass and both physical activity and muscular strength. There is a paucity of information describing the specific type of exercise which most benefits the human skeleton. The effects of a 1 yr weight training program on 18 middle-aged women participating in an endurance dance program (E + W) compared with 17 other women in the endurance dance program only (E) and with 19 sedentary controls (C) were studied by measuring muscular strength and bone mineral density (BMD). Eighteen women in the E + W group demonstrated increases in all strength measurements, whereas the E and C groups either had smaller increases or had declined. A significant group x test interaction term, indicating that groups responded differently over time, was observed for nondominant isokinetic elbow flexion measured through the range of motion at a constant velocity of 60 degrees.s-1 (P less than 0.05), nondominant isokinetic elbow extension at 180 degrees.s-1 (P less than 0.01), and nondominant isokinetic elbow flexion at 180 degrees.s-1 (P less than 0.05). BMD did not change significantly except that a significant group x test interaction term appeared for the radius ultradistal site (P less than 0.01). BMD of the humerus and femoral Ward's triangle increased nonsignificantly in both E and E + W over the year. This weight training program increased muscular strength but did not increase measured bone mass.
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Affiliation(s)
- S E Peterson
- Department of Preventive Medicine, University of Wisconsin, Madison 53705
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16
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Mitchell D, Peterson SE. Comment: oral cephalosporins. DICP 1990; 24:642-4. [PMID: 2360346 DOI: 10.1177/106002809002400621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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Abstract
Inappropriate laboratory use by physicians is partly responsible for the rapid rise in health care costs. This use falls into three categories--over-, under-, and misutilization. Overuse creates information overload for the physician and has a detrimental effect on patient care. Abnormal results are frequently obscured by massive amounts of requested information. Studies show that laboratory use is greater for younger physicians and that increased use is not associated with better outcome of care. Overuse ranges from 26 per cent to 98 per cent for selected tests. Unnecessary tests can be eliminated with no adverse effect on quality. Laboratory use can be improved by a variety of approaches including education, feedback, implementation of administrative changes and, finally, financial incentives or disincentives; the last has proven the most effective. All the approaches should be reinforced by cost-conscious clinical settings that foster a "why" rather than a "why not" philosophy. Improving laboratory use may reduce costs and maintain quality.
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Peterson SE, Rodin AE. Ohio's medical schools compared to other states: size and cost. Ohio State Med J 1983; 79:821-9. [PMID: 6646559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
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19
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Abstract
After four years of study in the United States, the Graduate Medical Education National Advisory Committee (GMENAC) concluded that an excess of approximately 70,000 physicians will exist in 1990. Faced with a future surplus, GMENAC recommends that U.S. medical schools decrease enrollment levels by 10 percent relative to the 1978-79 level and severely restrict entrance of foreign medical graduates. Flaws identified in the GMENAC approach relate to the use of the delphi technique, the future role of nonphysician providers, and a lack of reliable data. The GMENAC report may provide impetus for an abrupt shift from expansionism to reductionism in U.S. physician manpower policy. Long range physician manpower planning has erred in the past, necessitating periodic reevaluation of national policy. A continuing balance between supply and demand, although ideal, can probably never be attained. Thus small adjustments in total supply and specialty mix will always be necessary. The GMENAC report, which is the most comprehensive study of U.S. physician manpower to date, requires serious consideration in this context.
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20
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Peterson SE, Rodin AE. Instruction in physical facility construction for medical students. J Med Educ 1982; 57:323-325. [PMID: 7062329 DOI: 10.1097/00001888-198204000-00009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
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21
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Peterson SE, Marcum D, Rodin AE. Evaluation and validation of a course in practice management for senior residents. Med Teach 1982; 4:144-148. [PMID: 24483766 DOI: 10.3109/01421598209025985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Many doctors reach the end of their specialist training to find that they need to cope well and efficiently with the business aspects of setting up and managing a medical practice-yet this has frequently been ignored in their education. This article describes the design and evaluation of a course in practice management offered to doctors near the end of their specialist training.
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22
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Peterson SE, Rodin AE. Influences on graduate medical education: an analysis of historical and contemporary specialty maldistribution. Ohio State Med J 1980; 76:636-40. [PMID: 7443128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
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23
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Peterson SE, Barton J. Self-directed learning. J Med Educ 1980; 55:476-477. [PMID: 7381896 DOI: 10.1097/00001888-198005000-00021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
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24
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Peterson SE, Trzebiatowski GL, Quilty JE. Community-based Practitioners as Medical Student Preceptors-Dispelling an Old Myth. Med Teach 1979; 1:311-313. [PMID: 24483308 DOI: 10.3109/01421597909014344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
This study was designed to compare the teaching abilities of community-based preceptors and university-based clinical faculty, as judged by two matched groups of students. On only one of 13 dimensions of clinical teaching was there a significant difference between the preceptors and university-based faculty: preceptors were reported to use demonstrations less than their university-based colleagues. The study shows that despite their other commitments and lack of formal training in didactic skills, community-based practitioners can provide sound educational experiences and, in the students' opinions, are as competent teachers as clinical, university-based faculty.
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Affiliation(s)
- S E Peterson
- Educational Consultant to Residency Programs, Department of Postgraduate Medicine and Continuing Education, Wright State University School of Medicine, Dayton, Ohio
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25
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Lewinnek GE, Peterson SE. A calcified fibrocartilagenous nodule in the ligamentum nuchae. Presenting as a tumor. Clin Orthop Relat Res 1978:163-5. [PMID: 729280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Nodules of fibrocartilage, calcified fibrocartilage, or bone may be found in the adult ligamentum nuchae. These are generally asymptomatic but may mimic fractures or, as in the case presented here, tumors.
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