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Walton NA, Hafen B, Graceffo S, Sutherland N, Emmerson M, Palmquist R, Formea CM, Purcell M, Heale B, Brown MA, Danford CJ, Rachamadugu SI, Person TN, Shortt KA, Christensen GB, Evans JM, Raghunath S, Johnson CP, Knight S, Le VT, Anderson JL, Van Meter M, Reading T, Haslem DS, Hansen IC, Batcher B, Barker T, Sheffield TJ, Yandava B, Taylor DP, Ranade-Kharkar P, Giauque CC, Eyring KR, Breinholt JW, Miller MR, Carter PR, Gillman JL, Gunn AW, Knowlton KU, Bonkowsky JL, Stefansson K, Nadauld LD, McLeod HL. The Development of an Infrastructure to Facilitate the Use of Whole Genome Sequencing for Population Health. J Pers Med 2022; 12:jpm12111867. [PMID: 36579594 PMCID: PMC9693138 DOI: 10.3390/jpm12111867] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 10/29/2022] [Accepted: 11/04/2022] [Indexed: 11/09/2022] Open
Abstract
The clinical use of genomic analysis has expanded rapidly resulting in an increased availability and utility of genomic information in clinical care. We have developed an infrastructure utilizing informatics tools and clinical processes to facilitate the use of whole genome sequencing data for population health management across the healthcare system. Our resulting framework scaled well to multiple clinical domains in both pediatric and adult care, although there were domain specific challenges that arose. Our infrastructure was complementary to existing clinical processes and well-received by care providers and patients. Informatics solutions were critical to the successful deployment and scaling of this program. Implementation of genomics at the scale of population health utilizes complicated technologies and processes that for many health systems are not supported by current information systems or in existing clinical workflows. To scale such a system requires a substantial clinical framework backed by informatics tools to facilitate the flow and management of data. Our work represents an early model that has been successful in scaling to 29 different genes with associated genetic conditions in four clinical domains. Work is ongoing to optimize informatics tools; and to identify best practices for translation to smaller healthcare systems.
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Affiliation(s)
- Nephi A. Walton
- Intermountain Precision Genomics, Intermountain Healthcare, Salt Lake City, UT 84107, USA
- Correspondence:
| | - Brent Hafen
- Intermountain Precision Genomics, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Sara Graceffo
- Intermountain Precision Genomics, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Nykole Sutherland
- Intermountain Precision Genomics, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Melanie Emmerson
- Intermountain Precision Genomics, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Rachel Palmquist
- Department of Pediatrics, University of Utah, Salt Lake City, UT 84108, USA
- Center for Personalized Medicine, Primary Children’s Hospital, Intermountain Healthcare, Salt Lake City, UT 84113, USA
| | - Christine M. Formea
- Department of Pharmacy, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Maricel Purcell
- Intermountain Precision Genomics, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Bret Heale
- Humanized Health Consulting, Salt Lake City, UT 84102, USA
| | | | | | - Sumathi I. Rachamadugu
- Department of Bioinformatics and Genomics, Pennsylvania State University, University Park, PA 16802, USA
| | - Thomas N. Person
- John Hopkins Genomics—DNA Diagnostics Laboratory, Department of Genetic Medicine, John Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | | | - G. Bryce Christensen
- Intermountain Precision Genomics, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Jared M. Evans
- Intermountain Precision Genomics, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Sharanya Raghunath
- Intermountain Precision Genomics, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Christopher P. Johnson
- Intermountain Precision Genomics, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Stacey Knight
- Department of Cardiology, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Viet T. Le
- Department of Cardiology, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Jeffrey L. Anderson
- Department of Cardiology, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Margaret Van Meter
- Department of Medical Oncology, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Teresa Reading
- Department of Surgery, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Derrick S. Haslem
- Department of Cardiology, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Ivy C. Hansen
- School of Medicine, University of Utah, Salt Lake City, UT 84132, USA
| | - Betsey Batcher
- Department of Endocrinology, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Tyler Barker
- Intermountain Precision Genomics, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Travis J. Sheffield
- Intermountain Precision Genomics, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Bhaskara Yandava
- Digital Technology Services, Intermountain Healthcare, Salt Lake City, UT 84130, USA
| | - David P. Taylor
- Digital Technology Services, Intermountain Healthcare, Salt Lake City, UT 84130, USA
| | | | - Christopher C. Giauque
- Intermountain Precision Genomics, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Kenneth R. Eyring
- Intermountain Precision Genomics, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Jesse W. Breinholt
- Intermountain Precision Genomics, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Mickey R. Miller
- Intermountain Precision Genomics, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Payton R. Carter
- Intermountain Precision Genomics, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Jason L. Gillman
- Intermountain Precision Genomics, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Andrew W. Gunn
- Center for Personalized Medicine, Primary Children’s Hospital, Intermountain Healthcare, Salt Lake City, UT 84113, USA
| | - Kirk U. Knowlton
- Department of Cardiology, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Joshua L. Bonkowsky
- Department of Pediatrics, University of Utah, Salt Lake City, UT 84108, USA
- Center for Personalized Medicine, Primary Children’s Hospital, Intermountain Healthcare, Salt Lake City, UT 84113, USA
| | | | - Lincoln D. Nadauld
- Intermountain Precision Genomics, Intermountain Healthcare, Salt Lake City, UT 84107, USA
| | - Howard L. McLeod
- Intermountain Precision Genomics, Intermountain Healthcare, Salt Lake City, UT 84107, USA
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MERINO DM, Yee LM, McShane LM, Williams PM, Vilimas T, Patidar R, Barrett JC, Chen SJ, Cheng JH, Conroy JM, Cyanam D, Eyring KR, Fabrizio DA, Funari V, Garcia EP, Glenn ST, Gocke CD, Gupta V, Haley LM, Hellmann MD, Keefer L, Keeler LR, Kennedy B, Lazar AJ, MacConaill LE, Meier KL, Papin A, Rizvi NA, Sokol E, Stafford P, Thompson JF, Tom W, Weigman VJ, Xie M, Zhao C, Stewart MD, Allen J. Abstract 5671: Alignment of TMB measured on clinical samples: Phase IIB of the Friends of Cancer Research TMB Harmonization Project. Cancer Res 2020. [DOI: 10.1158/1538-7445.am2020-5671] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Introduction:
Tumor mutational burden (TMB) is the number of somatic mutations per megabase in a tumor's genome and has shown promise as a predictive biomarker of response to immune checkpoint inhibitors across several cancers. TMB is typically measured by whole exome sequencing (WES TMB) or by targeted next-generation sequencing gene panels (panel TMB). As more assays are developed to estimate TMB, harmonization is emerging as an unmet need and is a key goal of the Friends of Cancer Research (Friends) TMB Harmonization Project. Phase I of the Harmonization Project demonstrated correlation between panel TMB and WES TMB using TCGA data and defined theoretical sources of variability across panels. In phase IIA, sustainable TMB reference standard materials generated from human derived cell lines were used to characterize variability in TMB measurements across panels and assessed for utility in TMB alignment. Phase IIB aims to characterize variability in TMB measurements in clinical samples and to establish best practices for estimating and aligning TMB in order to improve consistency across panels.
Methods:
Fifteen laboratories (16 targeted gene panels) at different stages of development participated in phase IIB. Thirty formalin-fixed paraffin-embedded (FFPE) samples with >30% tumor content were acquired; tumor DNA was isolated by a single reference lab. TMB values were calculated for DNA extracted from lung (N=10), bladder (N=10), and gastric tumors (N=10) using WES and a uniform bioinformatics pipeline agreed upon by all Consortium members. DNA samples were also sent to all laboratories, and each used their own sequencing and bioinformatics pipelines to estimate TMB from the genes represented in their respective panels. For each tumor sample, a median across panel TMB estimates was calculated; individual panel TMB estimates were translated to fold-changes relative to the sample median to quantify variability. Association between WES TMB (reference) and panel TMB will be assessed by regression analysis; dependence of association on cancer type was investigated.
Results:
A subset of tumor samples (9 bladder, 7 lung, and 5 gastric) was analyzed using 11 panels at the time of abstract submission. Median panel TMB values ranged 0.60 - 40.26 across samples, with median of median values of 5.35. Fold-change from sample-level medians ranged 0x - 6.67x. Assessment of these clinical samples by WES and all 16 gene panels, as well as regression analysis results, are forthcoming.
Conclusions:
The Friends TMB Harmonization Project has made substantial progress in characterization of TMB measurement variability and association between WES TMB and panel TMB. These are important steps toward alignment of TMB estimates generated by different gene panels which may improve the interpretation of findings within clinical development programs and ultimately enhance the usefulness of this predictive biomarker in clinical decision making.
Citation Format: Diana M. MERINO, Laura M. Yee, Lisa M. McShane, P. Mickey Williams, Tomas Vilimas, Rajesh Patidar, J. Carl Barrett, Shu-Jen Chen, Jen-Hao Cheng, Jeffrey M. Conroy, Dinesh Cyanam, Kenneth R. Eyring, David A. Fabrizio, Vincent Funari, Elizabeth P. Garcia, Sean T. Glenn, Christopher D. Gocke, Vikas Gupta, Lisa M. Haley, Matthew D. Hellmann, Laurel Keefer, Lauryn R. Keeler, Brett Kennedy, Alexander J. Lazar, Laura E. MacConaill, Kristen L. Meier, Arnaud Papin, Naiyer A. Rizvi, Ethan Sokol, Phillip Stafford, John F. Thompson, Warren Tom, Victor J. Weigman, Mingchao Xie, Chen Zhao, Mark D. Stewart, Jeff Allen. Alignment of TMB measured on clinical samples: Phase IIB of the Friends of Cancer Research TMB Harmonization Project [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5671.
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Affiliation(s)
| | | | | | - P. Mickey Williams
- 3Molecular Characterization Laboratory, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc, Frederick, MD
| | - Tomas Vilimas
- 3Molecular Characterization Laboratory, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc, Frederick, MD
| | - Rajesh Patidar
- 3Molecular Characterization Laboratory, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc, Frederick, MD
| | | | | | | | | | | | | | | | | | | | | | | | | | - Lisa M. Haley
- 12Johns Hopkins University School of Medicine, Baltimore, MD
| | | | | | | | - Brett Kennedy
- 8Intermountain Precision Genomics, Salt Lake City, UT
| | | | | | | | | | | | | | | | | | - Warren Tom
- 22Thermo Fisher Scientific, South San Francisco, CA
| | | | | | | | | | - Jeff Allen
- 1Friends of Cancer Research, Washington, DC
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Eyring KR, Pedersen BS, Maclean KN, Stabler SP, Yang IV, Schwartz DA. Methylene-tetrahydrofolate reductase contributes to allergic airway disease. PLoS One 2018; 13:e0190916. [PMID: 29329322 PMCID: PMC5766142 DOI: 10.1371/journal.pone.0190916] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2017] [Accepted: 12/22/2017] [Indexed: 12/01/2022] Open
Abstract
Rationale Environmental exposures strongly influence the development and progression of asthma. We have previously demonstrated that mice exposed to a diet enriched with methyl donors during vulnerable periods of fetal development can enhance the heritable risk of allergic airway disease through epigenetic changes. There is conflicting evidence on the role of folate (one of the primary methyl donors) in modifying allergic airway disease. Objectives We hypothesized that blocking folate metabolism through the loss of methylene-tetrahydrofolate reductase (Mthfr) activity would reduce the allergic airway disease phenotype through epigenetic mechanisms. Methods Allergic airway disease was induced in C57BL/6 and C57BL/6Mthfr-/- mice through house dust mite (HDM) exposure. Airway inflammation and airway hyperresponsiveness (AHR) were measured between the two groups. Gene expression and methylation profiles were generated for whole lung tissue. Disease and molecular outcomes were evaluated in C57BL/6 and C57BL/6Mthfr-/- mice supplemented with betaine. Measurements and main results Loss of Mthfr alters single carbon metabolite levels in the lung and serum including elevated homocysteine and cystathionine and reduced methionine. HDM-treated C57BL/6Mthfr-/- mice demonstrated significantly less airway hyperreactivity (AHR) compared to HDM-treated C57BL/6 mice. Furthermore, HDM-treated C57BL/6Mthfr-/- mice compared to HDM-treated C57BL/6 mice have reduced whole lung lavage (WLL) cellularity, eosinophilia, and Il-4/Il-5 cytokine concentrations. Betaine supplementation reversed parts of the HDM-induced allergic airway disease that are modified by Mthfr loss. 737 genes are differentially expressed and 146 regions are differentially methylated in lung tissue from HDM-treated C57BL/6Mthfr-/- mice and HDM-treated C57BL/6 mice. Additionally, analysis of methylation/expression relationships identified 503 significant correlations. Conclusion Collectively, these findings indicate that the loss of folate as a methyl donor is a modifier of allergic airway disease, and that epigenetic and expression changes correlate with this modification. Further investigation into the mechanisms that drive this observation is warranted.
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Affiliation(s)
- Kenneth R. Eyring
- Department of Medicine, School of Medicine, University of Colorado, Aurora, CO, United States of America
| | - Brent S. Pedersen
- Department of Medicine, School of Medicine, University of Colorado, Aurora, CO, United States of America
| | - Kenneth N. Maclean
- Department of Pediatrics, School of Medicine, University of Colorado, Aurora, CO, United States of America
| | - Sally P. Stabler
- Department of Medicine, School of Medicine, University of Colorado, Aurora, CO, United States of America
| | - Ivana V. Yang
- Department of Medicine, School of Medicine, University of Colorado, Aurora, CO, United States of America
| | - David A. Schwartz
- Department of Medicine, School of Medicine, University of Colorado, Aurora, CO, United States of America
- Department of Immunology, School of Medicine, University of Colorado, Aurora, CO, United States of America
- * E-mail:
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