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Phung L, Wood E, Egleston B, Hoffman-Andrews L, Ofidis D, Howe S, Mim R, Griffin H, Fetzer D, Owens A, Domchek S, Pyeritz R, Katona B, Kallish S, Sirugo G, Weaver J, Nathanson KL, Rader DJ, Bradbury AR. Facilitating return of actionable genetic research results from a biobank repository: Participant uptake and utilization of digital interventions. HGG ADVANCES 2024; 5:100346. [PMID: 39183478 PMCID: PMC11415769 DOI: 10.1016/j.xhgg.2024.100346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 08/20/2024] [Accepted: 08/20/2024] [Indexed: 08/27/2024] Open
Abstract
Research participants report interest in receiving genetic research results. How best to return results remains unclear. In this randomized pilot study, we sought to assess the feasibility of returning actionable research results through a two-step process including a patient-centered digital intervention as compared with a genetic counselor (GC) in the Penn Medicine biobank. In Step 1, participants with an actionable result and procedural controls (no actionable result) were invited to digital pre-disclosure education and provided options for opting out of results. In Step 2, those with actionable results who had not opted out were randomized to receive results via a digital disclosure intervention or with a GC. Five participants (2%) opted out of results after Step 1. After both steps, 52 of 113 (46.0%) eligible cases received results, 5 (4.4%) actively declined results, 34 (30.1%) passively declined, and 22 (19.5%) could not be reached. Receiving results was associated with younger age (p < 0.001), completing pre-disclosure education (p < 0.001), and being in the GC arm (p = 0.06). Being older, female, and of Black race were associated with being unable to reach. Older age and Black race were associated with passively declining. Forty-seven percent of those who received results did not have personal or family history to suggest the mutation, and 55.1% completed clinical confirmation testing. The use of digital tools may be acceptable to participants and could reduce costs of returning results. Low uptake, disparities in uptake, and barriers to confirmation testing will be important to address to realize the benefit of returning actionable research results.
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Affiliation(s)
- Lillian Phung
- The University of Pennsylvania, Abramson Cancer Center and Division of Hematology-Oncology, Philadelphia, PA, USA
| | - Elisabeth Wood
- The University of Pennsylvania, Abramson Cancer Center and Division of Hematology-Oncology, Philadelphia, PA, USA
| | - Brian Egleston
- Fox Chase Cancer Center, Temple University, Philadelphia, PA, USA
| | - Lily Hoffman-Andrews
- The University of Pennsylvania, Division of Cardiovascular Medicine, Philadelphia, PA, USA
| | - Demetrios Ofidis
- The University of Pennsylvania, Abramson Cancer Center and Division of Hematology-Oncology, Philadelphia, PA, USA
| | - Sarah Howe
- The University of Pennsylvania, Abramson Cancer Center and Division of Hematology-Oncology, Philadelphia, PA, USA
| | - Rajia Mim
- The University of Pennsylvania, Abramson Cancer Center and Division of Hematology-Oncology, Philadelphia, PA, USA
| | - Hannah Griffin
- The University of Pennsylvania, Abramson Cancer Center and Division of Hematology-Oncology, Philadelphia, PA, USA
| | - Dominique Fetzer
- The University of Pennsylvania, Abramson Cancer Center and Division of Hematology-Oncology, Philadelphia, PA, USA
| | - Anjali Owens
- The University of Pennsylvania, Division of Cardiovascular Medicine, Philadelphia, PA, USA
| | - Susan Domchek
- The University of Pennsylvania, Abramson Cancer Center and Division of Hematology-Oncology, Philadelphia, PA, USA
| | - Reed Pyeritz
- The University of Pennsylvania, Division of Translational Medicine and Human Genetics, Philadelphia, PA, USA
| | - Bryson Katona
- The University of Pennsylvania, Division of Gastroenterology, Philadelphia, PA, USA
| | - Staci Kallish
- The University of Pennsylvania, Division of Translational Medicine and Human Genetics, Philadelphia, PA, USA
| | - Giorgio Sirugo
- The University of Pennsylvania, Division of Translational Medicine and Human Genetics, Philadelphia, PA, USA
| | - JoEllen Weaver
- The University of Pennsylvania, Division of Translational Medicine and Human Genetics, Philadelphia, PA, USA
| | - Katherine L Nathanson
- The University of Pennsylvania, Division of Translational Medicine and Human Genetics, Philadelphia, PA, USA
| | - Daniel J Rader
- The University of Pennsylvania, Division of Translational Medicine and Human Genetics, Philadelphia, PA, USA
| | - Angela R Bradbury
- The University of Pennsylvania, Abramson Cancer Center and Division of Hematology-Oncology, Philadelphia, PA, USA; The University of Pennsylvania, Department of Medical Ethics and Health Policy, Philadelphia, PA, USA.
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Stark Z, Glazer D, Hofmann O, Rendon A, Marshall CR, Ginsburg GS, Lunt C, Allen N, Effingham M, Hastings Ward J, Hill SL, Ali R, Goodhand P, Page A, Rehm HL, North KN, Scott RH. A call to action to scale up research and clinical genomic data sharing. Nat Rev Genet 2024:10.1038/s41576-024-00776-0. [PMID: 39375561 DOI: 10.1038/s41576-024-00776-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/29/2024] [Indexed: 10/09/2024]
Abstract
Genomic data from millions of individuals have been generated worldwide to drive discovery and clinical impact in precision medicine. Lowering the barriers to using these data collectively is needed to equitably realize the benefits of the diversity and scale of population data. We examine the current landscape of global genomic data sharing, including the evolution of data sharing models from data aggregation through to data visiting, and for certain use cases, cross-cohort analysis using federated approaches across multiple environments. We highlight emerging examples of best practice relating to participant, patient and community engagement; evolution of technical standards, tools and infrastructure; and impact of research and health-care policy. We outline 12 actions we can all take together to scale up efforts to enable safe global data sharing and move beyond projects demonstrating feasibility to routinely cross-analysing research and clinical data sets, optimizing benefit.
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Affiliation(s)
- Zornitza Stark
- Australian Genomics, Melbourne, Victoria, Australia.
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.
- University of Melbourne, Melbourne, Victoria, Australia.
| | - David Glazer
- Verily Life Sciences, South San Francisco, CA, USA.
| | - Oliver Hofmann
- Australian Genomics, Melbourne, Victoria, Australia
- University of Melbourne, Melbourne, Victoria, Australia
- University of Melbourne Centre for Cancer Research, Melbourne, Victoria, Australia
| | | | - Christian R Marshall
- Division of Genome Diagnostics, Pediatric Laboratory Medicine Department, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Geoffrey S Ginsburg
- All of Us Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Chris Lunt
- All of Us Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Naomi Allen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- UK Biobank, Stockport, UK
| | | | | | - Sue L Hill
- National Health Service England, London, UK
| | - Raghib Ali
- Our Future Health, Manchester, UK
- Oxford University Hospitals NHS Trust, Oxford, UK
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Peter Goodhand
- Global Alliance for Genomics and Health, Toronto, Ontario, Canada
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Angela Page
- Global Alliance for Genomics and Health, Toronto, Ontario, Canada
| | - Heidi L Rehm
- Global Alliance for Genomics and Health, Toronto, Ontario, Canada
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Kathryn N North
- Australian Genomics, Melbourne, Victoria, Australia
- University of Melbourne, Melbourne, Victoria, Australia
- Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Richard H Scott
- Genomics England, London, UK
- Great Ormond Street Hospital for Children, London, UK
- UCL Great Ormond Street Institute of Child Health, London, UK
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3
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Blair DR, Risch N. Dissecting the Reduced Penetrance of Putative Loss-of-Function Variants in Population-Scale Biobanks. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.09.23.24314008. [PMID: 39399029 PMCID: PMC11469360 DOI: 10.1101/2024.09.23.24314008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/15/2024]
Abstract
Loss-of-function variants (LoFs) disrupt the activity of their impacted gene. They are often associated with clinical phenotypes, including autosomal dominant diseases driven by haploinsufficiency. Recent analyses using biobanks have suggested that LoF penetrance for some haploinsufficient disorders may be low, an observation that has important implications for population genomic screening. However, biobanks are also rife with missing data, and the reliability of these findings remains uncertain. Here, we examine the penetrance of putative LoFs (pLoFs) using a cohort of ≈24,000 carriers derived from two population-scale biobanks: the UK Biobank and the All of Us Research Program. We investigate several possible etiologies for reduced pLoF penetrance, including biobank recruitment biases, annotation artifacts, missed diagnoses, and incomplete clinical records. Systematically accounting for these factors increased penetrance, but widespread reduced penetrance remained. Therefore, we hypothesized that other factors must be driving this phenomenon. To test this, we trained machine learning models to identify pLoFs with high penetrance using the genomic features specific to each variant. These models were predictive of penetrance across a range of diseases and ploF types, including those with prior evidence for pathogenicity. This suggests that reduced ploF penetrance is in fact common, and care should be taken when counseling asymptomatic carriers.
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Affiliation(s)
- David R. Blair
- Division of Medical Genetics, Department of Pediatrics
- University of California San Francisco
| | - Neil Risch
- Department of Epidemiology & Biostatistics
- University of California San Francisco
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Russo F, Chatterjee D, DeMaria N, Florido ME, Marasa M, Sabatello M, Wynn J, Milo Rasouly H. Negative results from DNA-based population screening for adult-onset diseases: the recipients' experience. J Community Genet 2024:10.1007/s12687-024-00736-5. [PMID: 39373866 DOI: 10.1007/s12687-024-00736-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2024] [Accepted: 09/17/2024] [Indexed: 10/08/2024] Open
Abstract
DNA-based population screening for adult-onset diseases holds promise for advancing personalized medicine and improving public health. Yet as most individuals pursuing such screening receive negative results, the return of results process must ensure that negative results and their implications are clearly understood. We explored the experiences of adults who received negative results from such screening as part of the Electronic Medical Records and Genomics consortium Phase 3 project (eMERGE-3) at Columbia University. In addition to a laboratory report and a standard counseling letter explaining the negative results, participants were randomized to receive (or not) a vignette explaining the results. A diverse cohort of 437 adult participants completed both baseline and post-result surveys. Many participants reported motivations that did not match the screening goals and included hope for diagnosis and family disease risk. A quarter of participants reported not feeling confident explaining their results to others (n = 105, 24%), and those who did not receive the vignette were less confident than those who did (29% versus 19% respectively; p-value = 0.02). Open-text responses about personal and family members' reactions to the results suggested that some perceived an exaggerated benefit from the negative result and might forgo more appropriate genetic testing. Our findings highlight the complexity of returning negative results and raise concerns that participants might forgo more suitable genetic testing. Future research is needed to compare the efficacy of different forms of ancillary materials on individuals' comprehension of negative results.
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Affiliation(s)
- Felicia Russo
- Division of Nephrology, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Genetic Counseling Graduate Program, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Debanjana Chatterjee
- Division of Nephrology, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Natalia DeMaria
- Division of Nephrology, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Michelle E Florido
- Genetic Counseling Graduate Program, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
- Department of Genetics and Development, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Maddalena Marasa
- Division of Nephrology, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Center for Precision Medicine and Genomics, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Maya Sabatello
- Center for Precision Medicine and Genomics, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Division of Ethics, Department of Medical Humanities and Ethics, Columbia University Irving Medical Center, New York, NY, USA
| | - Julia Wynn
- Genetic Counseling Graduate Program, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Hila Milo Rasouly
- Division of Nephrology, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA.
- Center for Precision Medicine and Genomics, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA.
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5
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Justice A, Kelly MA, Bellus G, Green JD, Zaidi R, Kerrins T, Josyula N, Luperchio TR, Kozel BA, Williams MS. Phenotypic Findings Associated with Variation in Elastin. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.09.10.24313340. [PMID: 39314928 PMCID: PMC11419209 DOI: 10.1101/2024.09.10.24313340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/25/2024]
Abstract
Variation in the elastin gene ( ELN ) may contribute to connective tissue disease beyond the known disease associations of Supravalvar Aortic Stenosis and Cutis Laxa. Exome data from MyCode Community Health Initiative participants were analyzed for ELN rare variants (mean allele frequency <1%, not currently annotated as benign). Participants with variants of interest underwent phenotyping by dual chart review using a standardized abstraction tool. Additionally, all rare variants that met inclusion criteria were collapsed into an ELN gene burden score to perform a Phenome-wide Association Study (PheWAS). Two hundred and ninety-six eligible participants with relevant ELN variants were identified from 184,293 MyCode participants. One hundred and three of 254 living participants (41%) met phenotypic criteria, most commonly aortic hypoplasia, arterial dilation, aneurysm, and dissection, and connective tissue abnormalities. ELN variation was significantly (P <2.8×10 -5 ) associated with "arterial dissection" in the PheWAS and two connective tissue Phecodes approached significance. Variation in ELN is associated with connective tissue pathology beyond classic phenotypes. eTOC Blurb Carriers of variants of interest in the elastin gene ( ELN ) were evaluated for presence of findings that could be associated with the variation. Chart review and Phenome-wide Association Studies were used. Results are consistent with variation in ELN being associated with findings affecting elastic tissues beyond classic phenotypes.
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Jones LK, Campbell-Salome G, Walters NL, Brangan A, Morgan KM, Tricou EP, Lindsey Mills ZT, McGowan MP, Gidding SS, Johns AM, Kirchner HL, Rahm AK, Sturm AC. IMPACT-FH Study for Implementing Innovative Family Communication and Cascade Testing Strategies for Familial Hypercholesterolemia. JACC. ADVANCES 2024; 3:101198. [PMID: 39238848 PMCID: PMC11375316 DOI: 10.1016/j.jacadv.2024.101198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Revised: 06/11/2024] [Accepted: 06/18/2024] [Indexed: 09/07/2024]
Abstract
Background Relatives of probands diagnosed with familial hypercholesterolemia (FH) should undergo cascade testing for FH. Objectives The purpose of this study was to evaluate probands' choices of innovative strategies to communicate their FH result with relatives and facilitate cascade testing uptake. Methods Probands with an FH genetic result from the MyCode Community Health Initiative could choose to share their FH result with adult blood relatives via the Family and Healthcare Professional Packet (packet), family sharing and cascade chatbots (chatbot), and/or FH Outreach and Support Program (direct contact). Cascade testing uptake was measured as reported completion of genetic or cholesterol testing. Generalized estimating equations models were used to identify factors associated with testing. Results One hundred seventy five probands received an FH result, median age was 58.9 (IQR: 44.9-69.3), and 58.9% were female. Probands shared information about 1,915 adult and 163 minor relatives (11.9 relatives per proband). Seventy percent of probands (121/175) selected at least one strategy for at least one adult relative. An average of 1.2 strategies was selected per adult relative. Cascade testing was completed for 26.6% (144/541) of adults with at least one strategy selected, 2.4% (33/1,374) of adults without a strategy selected, and 25.2% (41/163) of minor relatives. Factors associated with increased cascade testing uptake were selection of at least one strategy (6.32 higher odds), specifically, selection of direct contact (16.78 higher odds). Conclusions Strategies implemented improved FH cascade testing uptake compared to previous estimates and in families where no strategy was selected. Overall uptake remains insufficient, which can be attributed to probands reluctance to select a strategy for many relatives.
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Affiliation(s)
- Laney K Jones
- Department of Genomic Health, Research Institute, Geisinger, Danville, Pennsylvania, USA
- Heart and Vascular Institute, Geisinger, Danville, Pennsylvania, USA
| | - Gemme Campbell-Salome
- Department of Genomic Health, Research Institute, Geisinger, Danville, Pennsylvania, USA
- Department of Population Health Sciences, Research Institute, Geisinger, Danville, Pennsylvania, USA
| | - Nicole L Walters
- Department of Genomic Health, Research Institute, Geisinger, Danville, Pennsylvania, USA
| | - Andrew Brangan
- Department of Genomic Health, Research Institute, Geisinger, Danville, Pennsylvania, USA
| | - Kelly M Morgan
- Department of Genomic Health, Research Institute, Geisinger, Danville, Pennsylvania, USA
| | | | - Zoe T Lindsey Mills
- Department of Genomic Health, Research Institute, Geisinger, Danville, Pennsylvania, USA
| | | | - Samuel S Gidding
- Department of Genomic Health, Research Institute, Geisinger, Danville, Pennsylvania, USA
| | - Alicia M Johns
- Biostatistics Core, Research Institute, Geisinger, Danville, Pennsylvania, USA
| | - H Lester Kirchner
- Department of Population Health Sciences, Research Institute, Geisinger, Danville, Pennsylvania, USA
| | - Alanna Kulchak Rahm
- Department of Genomic Health, Research Institute, Geisinger, Danville, Pennsylvania, USA
| | - Amy C Sturm
- Department of Genomic Health, Research Institute, Geisinger, Danville, Pennsylvania, USA
- Heart and Vascular Institute, Geisinger, Danville, Pennsylvania, USA
- 23andMe, Sunnyvale, California, USA
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7
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Morgan KM, Campbell-Salome G, Walters NL, Betts MN, Brangan A, Johns A, Kirchner HL, Lindsey-Mills Z, McGowan MP, Tricou EP, Rahm AK, Sturm AC, Jones LK. Innovative Implementation Strategies for Familial Hypercholesterolemia Cascade Testing: The Impact of Genetic Counseling. J Pers Med 2024; 14:841. [PMID: 39202032 PMCID: PMC11355397 DOI: 10.3390/jpm14080841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2024] [Revised: 08/02/2024] [Accepted: 08/06/2024] [Indexed: 09/03/2024] Open
Abstract
The IMPACT-FH study implemented strategies (packet, chatbot, direct contact) to promote family member cascade testing for familial hypercholesterolemia (FH). We evaluated the impact of genetic counseling (GC) on medical outcomes, strategy selection, and cascade testing. Probands (i.e., patients with FH) were recommended to complete GC and select sharing strategies. Comparisons were performed for both medical outcomes and strategy selection between probands with or without GC. GEE models for Poisson regression were used to examine the relationship between proband GC completion and first-degree relative (FDR) cascade testing. Overall, 46.3% (81/175) of probands completed GC. Probands with GC had a median LDL-C reduction of -13.0 mg/dL (-61.0, 4.0) versus -1.0 mg/dL (-16.0, 17.0) in probands without GC (p = 0.0054). Probands with and without GC selected sharing strategies for 65.3% and 40.3% of FDRs, respectively (p < 0.0001). Similarly, 27.1% of FDRs of probands with GC completed cascade testing, while 12.0% of FDRs of probands without GC completed testing (p = 0.0043). Direct contact was selected for 47 relatives in total and completed for 39, leading to the detection of 18 relatives with FH. Proband GC was associated with improved medical outcomes and increased FDR cascade testing. Direct contact effectively identified FH cases for the subset who participated.
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Affiliation(s)
- Kelly M. Morgan
- Department of Genomic Health, Research Institute, Geisinger, 100 N. Academy Avenue, Danville, PA 17922, USA; (G.C.-S.); (N.L.W.); (A.B.); (Z.L.-M.); (A.C.S.)
| | - Gemme Campbell-Salome
- Department of Genomic Health, Research Institute, Geisinger, 100 N. Academy Avenue, Danville, PA 17922, USA; (G.C.-S.); (N.L.W.); (A.B.); (Z.L.-M.); (A.C.S.)
- Department of Population Health Sciences, Research Institute, Geisinger, 100 N. Academy Avenue, Danville, PA 17922, USA;
| | - Nicole L. Walters
- Department of Genomic Health, Research Institute, Geisinger, 100 N. Academy Avenue, Danville, PA 17922, USA; (G.C.-S.); (N.L.W.); (A.B.); (Z.L.-M.); (A.C.S.)
| | - Megan N. Betts
- WellSpan Health, 605 S. George Street, York, PA 17401, USA;
| | - Andrew Brangan
- Department of Genomic Health, Research Institute, Geisinger, 100 N. Academy Avenue, Danville, PA 17922, USA; (G.C.-S.); (N.L.W.); (A.B.); (Z.L.-M.); (A.C.S.)
| | - Alicia Johns
- Biostatistics Core, Research Institute, Geisinger, 100 N. Academy Avenue, Danville, PA 17922, USA;
| | - H. Lester Kirchner
- Department of Population Health Sciences, Research Institute, Geisinger, 100 N. Academy Avenue, Danville, PA 17922, USA;
| | - Zoe Lindsey-Mills
- Department of Genomic Health, Research Institute, Geisinger, 100 N. Academy Avenue, Danville, PA 17922, USA; (G.C.-S.); (N.L.W.); (A.B.); (Z.L.-M.); (A.C.S.)
| | - Mary P. McGowan
- Family Heart Foundation, 605 E. Colorado Blvd Ste 180, Pasadena, CA 91101, USA (E.P.T.)
| | - Eric P. Tricou
- Family Heart Foundation, 605 E. Colorado Blvd Ste 180, Pasadena, CA 91101, USA (E.P.T.)
| | - Alanna Kulchak Rahm
- Department of Genomic Health, Research Institute, Geisinger, 100 N. Academy Avenue, Danville, PA 17922, USA; (G.C.-S.); (N.L.W.); (A.B.); (Z.L.-M.); (A.C.S.)
| | - Amy C. Sturm
- Department of Genomic Health, Research Institute, Geisinger, 100 N. Academy Avenue, Danville, PA 17922, USA; (G.C.-S.); (N.L.W.); (A.B.); (Z.L.-M.); (A.C.S.)
- Heart and Vascular Institute, Geisinger, 100 N. Academy Avenue, Danville, PA 17922, USA
- 23andMe, 223 N. Mathilda Avenue, Sunnyvale, CA 94086, USA
| | - Laney K. Jones
- Department of Genomic Health, Research Institute, Geisinger, 100 N. Academy Avenue, Danville, PA 17922, USA; (G.C.-S.); (N.L.W.); (A.B.); (Z.L.-M.); (A.C.S.)
- Heart and Vascular Institute, Geisinger, 100 N. Academy Avenue, Danville, PA 17922, USA
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8
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Mauer Hall CB, Reys BD, Gemmell AP, Campbell CL, Pirzadeh-Miller SM. Downstream Revenue Generated by Patients With Hereditary Cancer in the Multigene Panel Testing Era. JCO Oncol Pract 2024:OP2300817. [PMID: 38815190 DOI: 10.1200/op.23.00817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 03/16/2024] [Accepted: 04/02/2024] [Indexed: 06/01/2024] Open
Abstract
PURPOSE Patients with hereditary cancer syndromes face increased medical management recommendations to address their cancer risks. As multigene panels are the standard of testing today, more patients needing clinical intervention are being identified. This study calculates the downstream revenue (DSR) generated by patients ascertained by a genetic counselor (GC) with a hereditary cancer likely pathogenic/pathogenic variant (LPV/PV). METHODS Retrospective chart review was performed for patients seen in a high-volume cancer genetics clinic between October 1, 2009, and December 31, 2021, with LPV/PVs in hereditary cancer predisposition genes. DSR and work relative value units (wRVUs) were calculated for each patient before and after they met with a GC. Subgroup analyses calculated DSR/wRVUs from patients affected and unaffected with cancer and those whose genetic counseling visit was the first at the institution (naїve). RESULTS A total of 978 patients were available for analysis after exclusions were applied. Patients generated $73.06 million (M) in US dollars (USD) in DSR and 54,814 wRVUs after their initial genetic counseling visit. Unaffected patients (n = 370, 37.8%) generated $11.38M (USD) and 13,879 wRVUs; affected patients (n = 608, 62.2%) generated $61.68M (USD) and 40,935 wRVUs. Naïve patients (n = 367, 37.5%) generated $15.39M (USD) and 11,811 wRVUs; established patients (n = 611, 62.5%) generated $57.67M (USD) and 43,003 wRVUs. Unaffected, naïve patients (n = 204, 20.9%) generated $5.48M (USD) and 5,186 wRVUs. CONCLUSION By identifying patients with hereditary cancer, GCs can bring in substantial DSR for their institution. Naïve and unaffected patients provide the greatest GC value-add as these patients represent new business and revenue sources to the institution. As multigene panels continue to expand, the number of patients needing downstream services will increase. Recognizing patients at increased cancer risk will improve patient outcomes while simultaneously providing DSR for institutions.
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Affiliation(s)
- Caitlin B Mauer Hall
- Department of Health Care Sciences, University of Texas Southwestern Medical Center, Dallas, TX
| | - Brian D Reys
- Cancer Genetics, University of Texas Southwestern Medical Center, Dallas, TX
| | - Amber P Gemmell
- Cancer Genetics, University of Texas Southwestern Medical Center, Dallas, TX
| | - Connor L Campbell
- Simmons Comprehensive Cancer Center Finance, University of Texas Southwestern Medical Center, Dallas, TX
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Forrest IS, Duffy Á, Park JK, Vy HMT, Pasquale LR, Nadkarni GN, Cho JH, Do R. Genome-first evaluation with exome sequence and clinical data uncovers underdiagnosed genetic disorders in a large healthcare system. Cell Rep Med 2024; 5:101518. [PMID: 38642551 PMCID: PMC11148562 DOI: 10.1016/j.xcrm.2024.101518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 05/01/2023] [Accepted: 03/26/2024] [Indexed: 04/22/2024]
Abstract
Population-based genomic screening may help diagnose individuals with disease-risk variants. Here, we perform a genome-first evaluation for nine disorders in 29,039 participants with linked exome sequences and electronic health records (EHRs). We identify 614 individuals with 303 pathogenic/likely pathogenic or predicted loss-of-function (P/LP/LoF) variants, yielding 644 observations; 487 observations (76%) lack a corresponding clinical diagnosis in the EHR. Upon further investigation, 75 clinically undiagnosed observations (15%) have evidence of symptomatic untreated disease, including familial hypercholesterolemia (3 of 6 [50%] undiagnosed observations with disease evidence) and breast cancer (23 of 106 [22%]). These genetic findings enable targeted phenotyping that reveals new diagnoses in previously undiagnosed individuals. Disease yield is greater with variants in penetrant genes for which disease is observed in carriers in an independent cohort. The prevalence of P/LP/LoF variants exceeds that of clinical diagnoses, and some clinically undiagnosed carriers are discovered to have disease. These results highlight the potential of population-based genomic screening.
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Affiliation(s)
- Iain S Forrest
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Áine Duffy
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Joshua K Park
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ha My T Vy
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Center for Genomic Data Analytics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Louis R Pasquale
- Department of Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Eye and Vision Research Institute, New York Eye and Ear Infirmary of Mount Sinai, New York, NY 10003, USA
| | - Girish N Nadkarni
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Division of Data-driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Judy H Cho
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ron Do
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Center for Genomic Data Analytics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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10
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Liang JW, Christensen KD, Green RC, Kraft P. Evaluating the utility of multi-gene, multi-disease population-based panel testing accounting for uncertainty in penetrance estimates. NPJ Genom Med 2024; 9:30. [PMID: 38760335 PMCID: PMC11101660 DOI: 10.1038/s41525-024-00414-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 04/19/2024] [Indexed: 05/19/2024] Open
Abstract
Panel germline testing allows for the efficient detection of deleterious variants for multiple conditions, but the benefits and harms of identifying these variants are not always well understood. We present a multi-gene, multi-disease aggregate utility formula that allows the user to consider adding or removing each gene in a panel based on variant frequency, estimated penetrances, and subjective disutilities for testing positive but not developing the disease and testing negative but developing the disease. We provide credible intervals for utility that reflect uncertainty in penetrance estimates. Rare, highly penetrant deleterious variants tend to contribute positive net utilities for a wide variety of user-specified disutilities, even when accounting for parameter estimation uncertainty. However, the clinical utility of deleterious variants with moderate, uncertain penetrance depends more on assumed disutilities. The decision to include a gene on a panel depends on variant frequency, penetrance, and subjective utilities and should account for uncertainties around these factors.
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Affiliation(s)
- Jane W Liang
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Kurt D Christensen
- Center for Healthcare Research in Pediatrics, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
- Department of Population Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Robert C Green
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Mass General Brigham, Boston, MA, USA
- Ariadne Labs, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Peter Kraft
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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11
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Allen CG, Hunt KJ, McMahon LL, Thornhill C, Jackson A, Clark JT, Kirchoff K, Garrison KL, Foil K, Malphrus L, Norman S, Ramos PS, Perritt K, Brown C, Lenert L, Judge DP. Using implementation science to evaluate a population-wide genomic screening program: Findings from the first 20,000 In Our DNA SC participants. Am J Hum Genet 2024; 111:433-444. [PMID: 38307026 PMCID: PMC10940017 DOI: 10.1016/j.ajhg.2024.01.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 01/04/2024] [Accepted: 01/04/2024] [Indexed: 02/04/2024] Open
Abstract
We use the implementation science framework RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) to describe outcomes of In Our DNA SC, a population-wide genomic screening (PWGS) program. In Our DNA SC involves participation through clinical appointments, community events, or at home collection. Participants provide a saliva sample that is sequenced by Helix, and those with a pathogenic variant or likely pathogenic variant for CDC Tier 1 conditions are offered free genetic counseling. We assessed key outcomes among the first cohort of individuals recruited. Over 14 months, 20,478 participants enrolled, and 14,053 samples were collected. The majority selected at-home sample collection followed by clinical sample collection and collection at community events. Participants were predominately female, White (self-identified), non-Hispanic, and between the ages of 40-49. Participants enrolled through community events were the most racially diverse and the youngest. Half of those enrolled completed the program. We identified 137 individuals with pathogenic or likely pathogenic variants for CDC Tier 1 conditions. The majority (77.4%) agreed to genetic counseling, and of those that agreed, 80.2% completed counseling. Twelve clinics participated, and we conducted 108 collection events. Participants enrolled at home were most likely to return their sample for sequencing. Through this evaluation, we identified facilitators and barriers to implementation of our state-wide PWGS program. Standardized reporting using implementation science frameworks can help generalize strategies and improve the impact of PWGS.
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Affiliation(s)
| | - Kelly J Hunt
- Medical University of South Carolina, Charleston, SC, USA
| | - Lori L McMahon
- Medical University of South Carolina, Charleston, SC, USA
| | - Clay Thornhill
- Medical University of South Carolina, Charleston, SC, USA
| | - Amy Jackson
- Medical University of South Carolina, Charleston, SC, USA
| | - John T Clark
- Medical University of South Carolina, Charleston, SC, USA
| | - Katie Kirchoff
- Medical University of South Carolina, Charleston, SC, USA
| | | | - Kimberly Foil
- Medical University of South Carolina, Charleston, SC, USA
| | - Libby Malphrus
- Medical University of South Carolina, Charleston, SC, USA
| | | | - Paula S Ramos
- Medical University of South Carolina, Charleston, SC, USA
| | - Kelly Perritt
- Medical University of South Carolina, Charleston, SC, USA
| | - Caroline Brown
- Medical University of South Carolina, Charleston, SC, USA
| | - Leslie Lenert
- Medical University of South Carolina, Charleston, SC, USA
| | - Daniel P Judge
- Medical University of South Carolina, Charleston, SC, USA
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12
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Schwartz MLB, McDonald WS, Hallquist MLG, Hu Y, McCormick CZ, Walters NL, Tsun J, Zimmerman K, Decker A, Gray C, Malinowski J, Sturm AC, Buchanan AH. Genetics Visit Uptake Among Individuals Receiving Clinically Actionable Genomic Screening Results. JAMA Netw Open 2024; 7:e242388. [PMID: 38488794 PMCID: PMC10943406 DOI: 10.1001/jamanetworkopen.2024.2388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 01/23/2024] [Indexed: 03/18/2024] Open
Abstract
Importance Screening unselected populations for clinically actionable genetic disease risk can improve ascertainment and facilitate risk management. Genetics visits may encourage at-risk individuals to perform recommended management, but little has been reported on genetics visit completion or factors associated with completion in genomic screening programs. Objective To identify factors associated with postdisclosure genetics visits in a genomic screening cohort. Design, Setting, and Participants This was a cohort study of biobank data in a health care system in central Pennsylvania. Participants' exome sequence data were reviewed for pathogenic or likely pathogenic (P/LP) results in all genes on the American College of Medical Genetics and Genomics Secondary Findings list. Clinically confirmed results were disclosed by phone and letter. Participants included adult MyCode biobank participants who received P/LP results between July 2015 and November 2019. Data were analyzed from May 2021 to March 2022. Exposure Clinically confirmed P/LP result disclosed by phone or letter. Main Outcomes and Measures Completion of genetics visit in which the result was discussed and variables associated with completion were assessed by electronic health record (EHR) review. Results Among a total of 1160 participants (703 [60.6%] female; median [IQR] age, 57.0 [42.1-68.5] years), fewer than half of participants (551 of 1160 [47.5%]) completed a genetics visit. Younger age (odds ratio [OR] for age 18-40 years, 2.98; 95% CI, 1.40-6.53; OR for age 41-65 years, 2.36; 95% CI, 1.22-4.74; OR for age 66-80 years, 2.60; 95% CI, 1.41-4.98 vs age ≥81 years); female sex (OR, 1.49; 95% CI, 1.14-1.96); being married (OR, 1.74; 95% CI, 1.23-2.47) or divorced (OR, 1.80; 95% CI, 1.11-2.91); lower Charlson comorbidity index (OR for score of 0-2, 1.76; 95% CI, 1.16-2.68; OR for score of 3-4, 1.73; 95% CI, 1.18-2.54 vs score of ≥5); EHR patient portal use (OR, 1.42; 95% CI, 1.06-1.89); living closer to a genetics clinic (OR, 1.64; 95% CI, 1.14-2.36 for <8.9 miles vs >20.1 miles); successful results disclosure (OR for disclosure by genetic counselor, 16.32; 95% CI, 8.16-37.45; OR for disclosure by research assistant, 20.30; 95% CI, 10.25-46.31 vs unsuccessful phone disclosure); and having a hereditary cancer result (OR, 2.13; 95% CI, 1.28-3.58 vs other disease risk) were significantly associated with higher rates of genetics visit completion. Preference to follow up with primary care was the most common reported reason for declining a genetics visit (68 of 152 patients [44.7%]). Conclusions and Relevance This cohort study of a biobank-based population genomic screening program suggests that targeted patient engagement, improving multidisciplinary coordination, and reducing barriers to follow-up care may be necessary for enhancing genetics visit uptake.
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Affiliation(s)
- Marci L. B. Schwartz
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
- Ted Rogers Centre for Heart Research, Cardiac Genome Clinic, Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, Ontario, Canada
| | | | | | - Yirui Hu
- Department of Population Health Sciences, Geisinger, Danville, Pennsylvania
| | | | | | - Jessica Tsun
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
| | | | - Amie Decker
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
- University of Arkansas Medical Sciences, Little Rock
| | - Celia Gray
- Phenomics and Clinical Data Core, Geisinger, Danville, Pennsylvania
| | | | - Amy C. Sturm
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
- 23andMe, Sunnyvale, California
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13
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Nolan J, Buchanan J, Taylor J, Almeida J, Bedenham T, Blair E, Broadgate S, Butler S, Cazeaux A, Craft J, Cranston T, Crawford G, Forrest J, Gabriel J, George E, Gillen D, Haeger A, Hastings Ward J, Hawkes L, Hodgkiss C, Hoffman J, Jones A, Karpe F, Kasperaviciute D, Kovacs E, Leigh S, Limb E, Lloyd-Jani A, Lopez J, Lucassen A, McFarlane C, O'Rourke AW, Pond E, Sherman C, Stewart H, Thomas E, Thomas S, Thomas T, Thomson K, Wakelin H, Walker S, Watson M, Williams E, Ormondroyd E. Secondary (additional) findings from the 100,000 Genomes Project: Disease manifestation, health care outcomes, and costs of disclosure. Genet Med 2024; 26:101051. [PMID: 38131308 DOI: 10.1016/j.gim.2023.101051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 12/15/2023] [Accepted: 12/15/2023] [Indexed: 12/23/2023] Open
Abstract
PURPOSE The UK 100,000 Genomes Project offered participants screening for additional findings (AFs) in genes associated with familial hypercholesterolemia (FH) or hereditary cancer syndromes including breast/ovarian cancer (HBOC), Lynch, familial adenomatous polyposis, MYH-associated polyposis, multiple endocrine neoplasia (MEN), and von Hippel-Lindau. Here, we report disclosure processes, manifestation of AF-related disease, outcomes, and costs. METHODS An observational study in an area representing one-fifth of England. RESULTS Data were collected from 89 adult AF recipients. At disclosure, among 57 recipients of a cancer-predisposition-associated AF and 32 recipients of an FH-associated AF, 35% and 88%, respectively, had personal and/or family history evidence of AF-related disease. During post-disclosure investigations, 4 cancer-AF recipients had evidence of disease, including 1 medullary thyroid cancer. Six women with an HBOC AF, 3 women with a Lynch syndrome AF, and 2 individuals with a MEN AF elected for risk-reducing surgery. New hyperlipidemia diagnoses were made in 6 FH-AF recipients and treatment (re-)initiated for 7 with prior hyperlipidemia. Generating and disclosing AFs in this region cost £1.4m; £8680 per clinically significant AF. CONCLUSION Generation and disclosure of AFs identifies individuals with and without personal or familial evidence of disease and prompts appropriate clinical interventions. Results can inform policy toward secondary findings.
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Affiliation(s)
- Joshua Nolan
- Radcliffe Department of Medicine, University of Oxford, United Kingdom
| | - James Buchanan
- Health Economics Research Centre, University of Oxford, United Kingdom
| | - John Taylor
- Oxford Genetic Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Joao Almeida
- Genomics England, United Kingdom Department of Health and Social Care, United Kingdom
| | - Tina Bedenham
- Oxford Genetic Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Edward Blair
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Suzanne Broadgate
- Oxford Genetic Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Samantha Butler
- Birmingham Women's and Children's Hospitals NHS Foundation Trust, Birmingham, United Kingdom
| | - Angela Cazeaux
- University Hospitals Southampton NHS Foundation Trust, Southampton, United Kingdom
| | - Judith Craft
- Oxford Genetic Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Treena Cranston
- Oxford Genetic Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Gillian Crawford
- University Hospitals Southampton NHS Foundation Trust, Southampton, United Kingdom
| | - Jamie Forrest
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; University of Manchester, Manchester, United Kingdom
| | - Jessica Gabriel
- Oxford Genetic Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Elaine George
- University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom
| | - Donna Gillen
- University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom
| | - Ash Haeger
- Oxford Genetic Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | | | - Lara Hawkes
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Claire Hodgkiss
- Oxford Genetic Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Jonathan Hoffman
- Birmingham Women's and Children's Hospitals NHS Foundation Trust, Birmingham, United Kingdom
| | - Alan Jones
- University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom
| | - Fredrik Karpe
- Radcliffe Department of Medicine, University of Oxford, United Kingdom; NIHR Oxford Biomedical Research Centre, Oxford, United Kingdom
| | - Dalia Kasperaviciute
- Genomics England, United Kingdom Department of Health and Social Care, United Kingdom
| | - Erika Kovacs
- University Hospitals Southampton NHS Foundation Trust, Southampton, United Kingdom
| | - Sarah Leigh
- Genomics England, United Kingdom Department of Health and Social Care, United Kingdom
| | - Elizabeth Limb
- Population Health Research Institute, St George's University of London, London, United Kingdom
| | - Anjali Lloyd-Jani
- Oxford Genetic Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Javier Lopez
- Genomics England, United Kingdom Department of Health and Social Care, United Kingdom
| | - Anneke Lucassen
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; Centre for Personalised Medicine, Nuffield Department of Medicine, University of Oxford, United Kingdom
| | - Carlos McFarlane
- Birmingham Women's and Children's Hospitals NHS Foundation Trust, Birmingham, United Kingdom
| | - Anthony W O'Rourke
- Oxford Genetic Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Emily Pond
- University Hospitals Southampton NHS Foundation Trust, Southampton, United Kingdom
| | - Catherine Sherman
- University Hospitals Southampton NHS Foundation Trust, Southampton, United Kingdom
| | - Helen Stewart
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Ellen Thomas
- Genomics England, United Kingdom Department of Health and Social Care, United Kingdom
| | - Simon Thomas
- University Hospitals Southampton NHS Foundation Trust, Southampton, United Kingdom
| | - Tessy Thomas
- University Hospitals Southampton NHS Foundation Trust, Southampton, United Kingdom
| | - Kate Thomson
- Oxford Genetic Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Hannah Wakelin
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Susan Walker
- Genomics England, United Kingdom Department of Health and Social Care, United Kingdom
| | - Melanie Watson
- University Hospitals Southampton NHS Foundation Trust, Southampton, United Kingdom
| | - Eleanor Williams
- Genomics England, United Kingdom Department of Health and Social Care, United Kingdom
| | - Elizabeth Ormondroyd
- Radcliffe Department of Medicine, University of Oxford, United Kingdom; NIHR Oxford Biomedical Research Centre, Oxford, United Kingdom.
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Horton C, Hoang L, Zimmermann H, Young C, Grzybowski J, Durda K, Vuong H, Burks D, Cass A, LaDuca H, Richardson ME, Harrison S, Chao EC, Karam R. Diagnostic Outcomes of Concurrent DNA and RNA Sequencing in Individuals Undergoing Hereditary Cancer Testing. JAMA Oncol 2024; 10:212-219. [PMID: 37924330 PMCID: PMC10625669 DOI: 10.1001/jamaoncol.2023.5586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 09/04/2023] [Indexed: 11/06/2023]
Abstract
Importance Personalized surveillance, prophylaxis, and cancer treatment options for individuals with hereditary cancer predisposition are informed by results of germline genetic testing. Improvements to genomic technology, such as the availability of RNA sequencing, may increase identification of individuals eligible for personalized interventions by improving the accuracy and yield of germline testing. Objective To assess the cumulative association of paired DNA and RNA testing with detection of disease-causing germline genetic variants and resolution of variants of uncertain significance (VUS). Design, Setting, and Participants Paired DNA and RNA sequencing was performed on individuals undergoing germline testing for hereditary cancer indication at a single diagnostic laboratory from March 2019 through April 2020. Demographic characteristics, clinical data, and test results were curated as samples were received, and changes to variant classification were assessed over time. Data analysis was performed from May 2020 to June 2023. Main Outcomes and Measures Main outcomes were increase in diagnostic yield, decrease in VUS rate, the overall results by variant type, the association of RNA evidence with variant classification, and the corresponding predicted effect on cancer risk management. Results A total of 43 524 individuals were included (median [range] age at testing, 54 [2-101] years; 37 373 female individuals [85.7%], 6224 male individuals [14.3%], and 2 individuals of unknown sex [<0.1%]), with 43 599 tests. A total of 2197 (5.0%) were Ashkenazi Jewish, 1539 (3.5%) were Asian, 3077 (7.1%) were Black, 2437 (5.6%) were Hispanic, 27 793 (63.7%) were White, and 2049 (4.7%) were other race, and for 4507 individuals (10.3%), race and ethnicity were unknown. Variant classification was impacted in 549 individuals (1.3%). Medically significant upgrades were made in 97 individuals, including 70 individuals who had a variant reclassified from VUS to pathogenic/likely pathogenic (P/LP) and 27 individuals who had a novel deep intronic P/LP variant that would not have been detected using DNA sequencing alone. A total of 93 of 545 P/LP splicing variants (17.1%) were dependent on RNA evidence for classification, and 312 of 439 existing splicing VUS (71.1%) were resolved by RNA evidence. Notably, the increase in positive rate (3.1%) and decrease in VUS rate (-3.9%) was higher in Asian, Black, and Hispanic individuals combined compared to White individuals (1.6%; P = .02; and -2.5%; P < .001). Conclusions and Relevance Findings of this diagnostic study demonstrate that the ability to perform RNA sequencing concurrently with DNA sequencing represents an important advancement in germline genetic testing by improving detection of novel variants and classification of existing variants. This expands the identification of individuals with hereditary cancer predisposition and increases opportunities for personalization of therapeutics and surveillance.
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Affiliation(s)
| | | | | | | | | | | | - Huy Vuong
- Ambry Genetics, Aliso Viejo, California
| | | | | | | | | | | | - Elizabeth C. Chao
- Ambry Genetics, Aliso Viejo, California
- University of California, Irvine, School of Medicine
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15
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Hutchcraft ML, Zhang S, Lin N, Pickarski JC, Belcher EA, Wei S, Bocklage T, Miller RW, Villano JL, Cavnar MJ, Kim J, Arnold SM, Ueland FR, Kolesar JM. Feasibility and Clinical Utility of Reporting Hereditary Cancer Predisposition Pathogenic Variants Identified in Research Germline Sequencing: A Prospective Interventional Study. JCO Precis Oncol 2024; 8:e2300266. [PMID: 38295319 PMCID: PMC10843325 DOI: 10.1200/po.23.00266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 11/02/2023] [Accepted: 12/04/2023] [Indexed: 02/02/2024] Open
Abstract
PURPOSE Patients with cancer frequently undergo research-grade germline sequencing but clinically actionable results are not routinely disclosed. The objective of this study is to evaluate the feasibility of reporting clinically relevant secondary findings (SF) identified in germline research sequencing using the institutional molecular tumor board (MTB) and the treating oncology physician. METHODS This prospective, interventional cohort study enrolled Total Cancer Care participants with any cancer diagnosis at a single institution. Patients underwent research-grade germline whole-exome sequencing, with bioinformatic analysis in a Clinical Laboratory Improvement Amendments-certified laboratory to verify pathogenic/likely pathogenic germline variants (PGVs) in any American College of Medical Genomics and Genetics SF v2.0 genes. After a protocol modification in consenting patients, the MTB reported PGVs to treating oncology physicians with recommendations for referral to a licensed genetic counselor and clinical confirmatory testing. RESULTS Of the 781 enrolled participants, 32 (4.1%) harbored cancer predisposition PGVs, 24 (3.1%) were heterozygous carriers of an autosomal recessive cancer predisposition syndrome, and 14 (1.8%) had other hereditary disease PGVs. Guideline-directed testing would have missed 37.5% (12/32) of the inherited cancer predisposition PGVs, which included BRCA1, BRCA2, MSH6, SDHAF2, SDHB, and TP53 variants. Three hundred fifteen participants consented to reporting results; results for all living patients were reported to the clinical team with half referred to a licensed genetic counselor. There was concordance between all research variants identified in patients (n = 9) who underwent clinical confirmatory sequencing. CONCLUSION MTB reporting of research-grade germline sequencing to the clinical oncology team is feasible. Over a third of PGVs identified using a universal testing strategy would have been missed by guideline-based approach, suggesting a role for expanding germline testing.
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Affiliation(s)
- Megan L. Hutchcraft
- Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, University of Kentucky Markey Comprehensive Cancer Center, Lexington, KY
| | - Shulin Zhang
- Department of Pathology and Laboratory Medicine University of Kentucky Chandler Medical Center, Lexington, KY
- Markey Comprehensive Cancer Center, University of Kentucky, Lexington, KY
| | - Nan Lin
- Department of Pharmacy Practice and Science, University of Kentucky College of Pharmacy, Lexington, KY
| | | | - Elizabeth A. Belcher
- Department of Clinical Research, University of Kentucky Markey Comprehensive Cancer Center, Lexington, KY
| | - Sainan Wei
- Department of Pathology and Laboratory Medicine University of Kentucky Chandler Medical Center, Lexington, KY
| | - Thèrése Bocklage
- Department of Pathology and Laboratory Medicine University of Kentucky Chandler Medical Center, Lexington, KY
| | - Rachel W. Miller
- Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, University of Kentucky Markey Comprehensive Cancer Center, Lexington, KY
| | - John L. Villano
- Division of Medical Oncology, Department of Internal Medicine, University of Kentucky Markey Comprehensive Cancer Center, Lexington, KY
| | - Michael J. Cavnar
- Division of Surgical Oncology, Department of Surgery, University of Kentucky Markey Comprehensive Cancer Center, Lexington, KY
| | - Joseph Kim
- Division of Surgical Oncology, Department of Surgery, University of Kentucky Markey Comprehensive Cancer Center, Lexington, KY
| | - Susanne M. Arnold
- Division of Medical Oncology, Department of Internal Medicine, University of Kentucky Markey Comprehensive Cancer Center, Lexington, KY
| | - Frederick R. Ueland
- Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, University of Kentucky Markey Comprehensive Cancer Center, Lexington, KY
| | - Jill M. Kolesar
- Markey Comprehensive Cancer Center, University of Kentucky, Lexington, KY
- Department of Pharmacy Practice and Science, University of Kentucky College of Pharmacy, Lexington, KY
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16
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Rao ND, King KM, Kaganovsky J, Hassan S, Tsinajinne D, Fullerton SM, Chen AT, Veenstra DL, Shirts BH. Risk perception and intended behavior change after uninformative genetic results for adult-onset hereditary conditions in unselected patients. Eur J Hum Genet 2024; 32:77-82. [PMID: 37752309 PMCID: PMC10772064 DOI: 10.1038/s41431-023-01460-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Revised: 08/16/2023] [Accepted: 09/11/2023] [Indexed: 09/28/2023] Open
Abstract
Population genetic screening for preventable adult-onset hereditary conditions may improve disease management and morbidity but most individuals will receive uninformative results that do not indicate higher risk for disease. Investigation into subsequent psychosocial health and behaviors is necessary to inform population screening feasibility, effectiveness, and cost considerations. We conducted a prospective survey study of unselected University of Washington Medicine patients enrolled in a genetic research study screening for pathogenic variation in medically important genes. Survey questions adapted from the Feelings About genomiC Testing Results (FACToR) questionnaire and designed to understand perceived disease risk change and planned health behaviors were administered after receipt of results. Overall, 2761 people received uninformative results and 1352 (49%) completed survey items. Respondents averaged 41 years old, 62% were female, and 56% were Non-Hispanic Asian. Results from the FACToR instrument showed mean (SD) scores of 0.92 (1.34), 7.63 (3.95), 1.65 (2.23), and 0.77 (1.50) for negative emotions, positive emotions, uncertainty, and privacy concerns, respectively, suggesting minimal psychosocial harms from genetic screening. Overall, 12.2% and 9.6% of survey respondents believed that their risk of cancer or heart disease, respectively, had changed after receiving their uninformative genetic screening results. Further, 8.5% of respondents planned to make healthcare changes and 9.1% other behavior changes. Future work is needed to assess observed behavior changes attributable to uninformative screening results and if small changes in behavior among this population have large downstream impacts.
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Affiliation(s)
- Nandana D Rao
- Institute for Public Health Genetics, University of Washington, Seattle, WA, USA
| | - Kristine M King
- Institute for Public Health Genetics, University of Washington, Seattle, WA, USA
| | - Jailanie Kaganovsky
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Sajida Hassan
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Darwin Tsinajinne
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Stephanie M Fullerton
- Department of Bioethics & Humanities, University of Washington School of Medicine, Seattle, WA, USA
| | - Annie T Chen
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA
| | - David L Veenstra
- The Comparative Health Outcomes, Policy & Economics (CHOICE) Institute, Department of Pharmacy, University of Washington, Seattle, WA, USA
| | - Brian H Shirts
- Institute for Public Health Genetics, University of Washington, Seattle, WA, USA.
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA.
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17
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Wu BU, Chen Q, Moon BH, Lustigova E, Nielsen EG, Alvarado M, Ahmed SA. Association of Glycated Hemoglobin With a Risk of Pancreatic Cancer in High-Risk Individuals Based on Genetic and Family History. Clin Transl Gastroenterol 2024; 15:e00650. [PMID: 37800692 PMCID: PMC10810597 DOI: 10.14309/ctg.0000000000000650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 09/21/2023] [Indexed: 10/07/2023] Open
Abstract
INTRODUCTION Screening for pancreatic cancer (PC) is suggested for high-risk individuals. Additional risk factors may enhance early detection in this population. METHODS Retrospective cohort study among patients with germline variants and/or familial pancreatic cancer in an integrated healthcare system between 2003 and 2019. We calculated the incidence rate (IR) by risk category and performed a nested case-control study to evaluate the relationship between HbA1C and PC within 3 years before diagnosis (cases) or match date (controls). Cases were matched 1:4 by age, sex, and timing of HbA1c. Logistic regression was performed to assess an independent association with PC. RESULTS We identified 5,931 high-risk individuals: 1,175(19.8%) familial PC, 45(0.8%) high-risk germline variants ( STK11, CDKN2A ), 4,097(69.1%) had other germline variants ( ATM, BRCA 1, BRCA 2, CASR, CDKN2A, CFTR, EPCAM, MLH1, MSH2, MSH6, PALB2, PRSS1, STK11, and TP53 ), and 614(10.4%) had both germline variants and family history. Sixty-eight patients (1.1%) developed PC; 50% were metastatic at diagnosis. High-risk variant was associated with greatest risk of PC, IR = 85.1(95% confidence interval: 36.7-197.6)/10,000 person-years; other germline variants and first-degree relative had IR = 33 (18.4, 59.3), whereas IR among ≥2 first-degree relative alone was 10.7 (6.1, 18.8). HbA1c was significantly higher among cases vs controls (median = 7.0% vs 6.4%, P = 0.02). In multivariable analysis, every 1% increase in HbA1c was associated with 36% increase in odds of PC (odds ratio 1.36, 95% confidence interval: 1.08-1.72). Pancreatitis was independently associated with a risk of PC (odds ratio 3.93, 95% confidence limit 1.19, 12.91). DISCUSSION Risk of PC varies among high-risk individuals. HbA1c and history of pancreatitis may be useful additional markers for early detection in this patient population.
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Affiliation(s)
- Bechien U. Wu
- Center for Pancreatic Care, Division of Gastroenterology, Kaiser Permanente Los Angeles Medical Center, Los Angeles, California, USA;
| | - Qiaoling Chen
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA;
| | - Becky H. Moon
- Center for Pancreatic Care, Division of Gastroenterology, Kaiser Permanente Los Angeles Medical Center, Los Angeles, California, USA;
| | - Eva Lustigova
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA;
| | - Erin G. Nielsen
- Department of Genetics, Southern California Medical Group, Pasadena, California, USA;
| | - Monica Alvarado
- Department of Genetics, Southern California Medical Group, Pasadena, California, USA;
| | - Syed A. Ahmed
- Department of Genetics, Kaiser Permanente Riverside Medical Center, Riverside, California, USA
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18
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Lacaze P, Marquina C, Tiller J, Brotchie A, Kang YJ, Merritt MA, Green RC, Watts GF, Nowak KJ, Manchanda R, Canfell K, James P, Winship I, McNeil JJ, Ademi Z. Combined population genomic screening for three high-risk conditions in Australia: a modelling study. EClinicalMedicine 2023; 66:102297. [PMID: 38192593 PMCID: PMC10772163 DOI: 10.1016/j.eclinm.2023.102297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 10/12/2023] [Accepted: 10/13/2023] [Indexed: 01/10/2024] Open
Abstract
Background No previous health-economic evaluation has assessed the impact and cost-effectiveness of offering combined adult population genomic screening for mutliple high-risk conditions in a national public healthcare system. Methods This modeling study assessed the impact of offering combined genomic screening for hereditary breast and ovarian cancer, Lynch syndrome and familial hypercholesterolaemia to all young adults in Australia, compared with the current practice of clinical criteria-based testing for each condition separately. The intervention of genomic screening, assumed as an up-front single cost in the first annual model cycle, would detect pathogenic variants in seven high-risk genes. The simulated population was 18-40 year-olds (8,324,242 individuals), modelling per-sample test costs ranging AU$100-$1200 (base-case AU$200) from the year 2023 onwards with testing uptake of 50%. Interventions for identified high-risk variant carriers follow current Australian guidelines, modelling imperfect uptake and adherence. Outcome measures were morbidity and mortality due to cancer (breast, ovarian, colorectal and endometrial) and coronary heart disease (CHD) over a lifetime horizon, from healthcare-system and societal perspectives. Outcomes included quality-adjusted life years (QALYs) and incremental cost-effectiveness ratio (ICER), discounted 5% annually (with 3% discounting in scenario analysis). Findings Over the population lifetime (to age 80 years), the model estimated that genomic screening per-100,000 individuals would lead to 747 QALYs gained by preventing 63 cancers, 31 CHD cases and 97 deaths. In the total model population, this would translate to 31,094 QALYs gained by preventing 2612 cancers, 542 non-fatal CHD events and 4047 total deaths. At AU$200 per-test, genomic screening would require an investment of AU$832 million for screening of 50% of the population. Our findings suggest that this intervention would be cost-effective from a healthcare-system perspective, yielding an ICER of AU$23,926 (∼£12,050/€14,110/US$15,345) per QALY gained over the status quo. In scenario analysis with 3% discounting, an ICER of AU$4758/QALY was obtained. Sensitivity analysis for the base case indicated that combined genomic screening would be cost-effective under 70% of simulations, cost-saving under 25% and not cost-effective under 5%. Threshold analysis showed that genomic screening would be cost-effective under the AU$50,000/QALY willingness-to-pay threshold at per-test costs up to AU$325 (∼£164/€192/US$208). Interpretation Our findings suggest that offering combined genomic screening for high-risk conditions to young adults would be cost-effective in the Australian public healthcare system, at currently realistic testing costs. Other matters, including psychosocial impacts, ethical and societal issues, and implementation challenges, also need consideration. Funding Australian Government, Department of Health, Medical Research Future Fund, Genomics Health Futures Mission (APP2009024). National Heart Foundation Future Leader Fellowship (102604).
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Affiliation(s)
- Paul Lacaze
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - Clara Marquina
- Health Economics and Policy Evaluation Research (HEPER) Group, Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, VIC 3052, Australia
| | - Jane Tiller
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - Adam Brotchie
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - Yoon-Jung Kang
- The Daffodil Centre, The University of Sydney, A Joint Venture with Cancer Council NSW, Sydney, NSW 2011, Australia
| | - Melissa A. Merritt
- The Daffodil Centre, The University of Sydney, A Joint Venture with Cancer Council NSW, Sydney, NSW 2011, Australia
| | - Robert C. Green
- Mass General Brigham, Broad Institute, Ariadne Labs and Harvard Medical School, Boston, MA, 02114, USA
| | - Gerald F. Watts
- School of Medicine, University of Western Australia, Perth, WA 6009, Australia
- Departments of Cardiology and Internal Medicine, Royal Perth Hospital, Perth, WA, 6001, Australia
| | - Kristen J. Nowak
- Public and Aboriginal Health Division, Western Australia Department of Health, East Perth, WA, 6004, Australia
- Centre for Medical Research, The University of Western Australia, Crawley, WA, 6009, Australia
| | - Ranjit Manchanda
- Wolfson Institute of Population Health, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
- Department of Health Services Research, Faculty of Public Health & Policy, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK
| | - Karen Canfell
- The Daffodil Centre, The University of Sydney, A Joint Venture with Cancer Council NSW, Sydney, NSW 2011, Australia
| | - Paul James
- Parkville Familial Cancer Centre, Peter McCallum Cancer Centre, Melbourne, VIC, 3000, Australia
- Department of Genomic Medicine, Royal Melbourne Hospital City Campus, Parkville, VIC, 3050, Australia
- Department of Medicine, University of Melbourne, Parkville, VIC, 3050, Australia
| | - Ingrid Winship
- Department of Genomic Medicine, Royal Melbourne Hospital City Campus, Parkville, VIC, 3050, Australia
- Department of Medicine, University of Melbourne, Parkville, VIC, 3050, Australia
| | - John J. McNeil
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - Zanfina Ademi
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
- Health Economics and Policy Evaluation Research (HEPER) Group, Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, VIC 3052, Australia
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19
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Allen CG, McBride CM, Escoffery C, Guan Y, Hood C, Zaho J, Brody G, An W. Developing and assessing a kin keeping scale with application to identifying central influencers in African American family networks. J Community Genet 2023; 14:593-603. [PMID: 37648941 PMCID: PMC10725405 DOI: 10.1007/s12687-023-00665-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 08/18/2023] [Indexed: 09/01/2023] Open
Abstract
Promoting family communication about inherited disease risk is an arena in which family systems theory is highly relevant. One family systems' construct that can support promotion of family communication regarding inherited disease risk is the notion of "kin keeping." However, kin keeping and whether it might be capitalized on to encourage family communication about inherited risk has been understudied. The goal of this report was to propose a broadened conceptualization of kin keeping that distinguishes between a structural functional perspective (role conceptualization) and transitional behaviors (skill conceptualization), and to develop and evaluate a scale that would enable this assertion to be tested among a sample of African American community health workers. We developed a scale using four steps: item development using concept analysis and content validity, scale development among a national sample (n = 312), scale evaluation using exploratory factor analysis (n = 52), and scale reduction. We then posed suppositions of associations that would indicate whether the developed kin keeping measure was assessing a specific family role or set of behaviors. Our results included the development of the first quantitative measure of kin keeping (9- and 15-item scales). Model fit for 9-item scale (CFI = 0.97, AFGI = 0.89, RMSEA = 0.09, SMRM = 0.06) and model fit for 15-item scale (CFI = 0.97, AFGI = 0.89, RMSEA = 0.06, SMRM = 0.05). These findings allow us to move toward more rigorous research about the role of kin keeping on information sharing and health decision making. Results also suggest that, contrary to the historical structural functional conceptualization of kin keeping as a role, kin keeping might also be conceptualized as a behavior or set of modifiable behaviors. Ultimately, the kin keeping scale could be used to operationalize kin keeping in various theoretical models and frameworks, guide intervention development to encourage or train for kin keeping behaviors, and test assumptions of whether families vary in the density of kin keeping.
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Affiliation(s)
- Caitlin G Allen
- Medical University of South Carolina, Charleston, SC, USA.
- Emory University, Atlanta, GA, USA.
| | | | | | - Yue Guan
- Emory University, Atlanta, GA, USA
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20
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Schwiter R, Rocha H, Johns A, Savatt JM, Diehl DL, Kelly MA, Williams MS, Buchanan AH. Low adenoma burden in unselected patients with a pathogenic APC variant. Genet Med 2023; 25:100949. [PMID: 37542411 DOI: 10.1016/j.gim.2023.100949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 07/28/2023] [Accepted: 07/28/2023] [Indexed: 08/06/2023] Open
Abstract
PURPOSE Genomic screening can improve clinical outcomes, but presentation of individuals with risk for polyposis identified via genomic screening is unknown. To inform assessment of clinical utility of genomic screening for polyposis risk, clinical presentation of individuals in an unselected health care system cohort with an APC pathogenic or likely pathogenic (P/LP) variant causative of familial adenomatous polyposis are described. METHODS Electronic health records of individuals with an APC P/LP variant identified via the MyCode program (MyCode APC+) were reviewed to assess adenoma burden and compare it among individuals with a clinical diagnosis of familial adenomatous polyposis and matched variant-negative controls. RESULTS The prevalence of APC P/LP variants in this health care cohort is estimated to be 1 in 2800. Twenty-four MyCode APC+ individuals were identified during the study period. Median age at result disclosure was 53 years. Rate of clinical polyposis was 8%. Two of six participants with a classic region variant and none of those with an attenuated region variant had polyposis. MyCode APC+ participants did not differ from controls in cumulative adenoma count. CONCLUSION APC P/LP variant prevalence estimate in the MyCode cohort is higher than prior published prevalence rates. Individuals with APC P/LP variants identified via genomic screening had a low adenoma burden.
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Affiliation(s)
| | - Heather Rocha
- Department of Genomic Health, Geisinger, Danville, PA
| | - Alicia Johns
- Department of Population Health Sciences, Geisinger, Danville, PA
| | | | - David L Diehl
- Department of Medicine, Division of Gastroenterology and Hepatology, Geisinger, Danville, PA
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21
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Watts GF, Gidding SS, Hegele RA, Raal FJ, Sturm AC, Jones LK, Sarkies MN, Al-Rasadi K, Blom DJ, Daccord M, de Ferranti SD, Folco E, Libby P, Mata P, Nawawi HM, Ramaswami U, Ray KK, Stefanutti C, Yamashita S, Pang J, Thompson GR, Santos RD. International Atherosclerosis Society guidance for implementing best practice in the care of familial hypercholesterolaemia. Nat Rev Cardiol 2023; 20:845-869. [PMID: 37322181 DOI: 10.1038/s41569-023-00892-0] [Citation(s) in RCA: 66] [Impact Index Per Article: 66.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/12/2023] [Indexed: 06/17/2023]
Abstract
This contemporary, international, evidence-informed guidance aims to achieve the greatest good for the greatest number of people with familial hypercholesterolaemia (FH) across different countries. FH, a family of monogenic defects in the hepatic LDL clearance pathway, is a preventable cause of premature coronary artery disease and death. Worldwide, 35 million people have FH, but most remain undiagnosed or undertreated. Current FH care is guided by a useful and diverse group of evidence-based guidelines, with some primarily directed at cholesterol management and some that are country-specific. However, none of these guidelines provides a comprehensive overview of FH care that includes both the lifelong components of clinical practice and strategies for implementation. Therefore, a group of international experts systematically developed this guidance to compile clinical strategies from existing evidence-based guidelines for the detection (screening, diagnosis, genetic testing and counselling) and management (risk stratification, treatment of adults or children with heterozygous or homozygous FH, therapy during pregnancy and use of apheresis) of patients with FH, update evidence-informed clinical recommendations, and develop and integrate consensus-based implementation strategies at the patient, provider and health-care system levels, with the aim of maximizing the potential benefit for at-risk patients and their families worldwide.
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Affiliation(s)
- Gerald F Watts
- School of Medicine, University of Western Australia, Perth, WA, Australia.
- Departments of Cardiology and Internal Medicine, Royal Perth Hospital, Perth, WA, Australia.
| | | | - Robert A Hegele
- Department of Medicine and Robarts Research Institute, Schulich School of Medicine, Western University, London, ON, Canada
| | - Frederick J Raal
- Department of Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Amy C Sturm
- Department of Genomic Health, Geisinger, Danville, PA, USA
- 23andMe, Sunnyvale, CA, USA
| | - Laney K Jones
- Department of Genomic Health, Geisinger, Danville, PA, USA
| | - Mitchell N Sarkies
- School of Health Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - Khalid Al-Rasadi
- Medical Research Centre, College of Medicine and Health Sciences, Sultan Qaboos University, Muscat, Oman
| | - Dirk J Blom
- Division of Lipidology and Cape Heart Institute, Department of Medicine, University of Cape Town, Cape Town, South Africa
| | | | | | | | - Peter Libby
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Pedro Mata
- Fundación Hipercolesterolemia Familiar, Madrid, Spain
| | - Hapizah M Nawawi
- Institute of Pathology, Laboratory and Forensic Medicine (I-PPerForM) and Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh, Selangor, Malaysia
- Specialist Lipid and Coronary Risk Prevention Clinics, Hospital Al-Sultan Abdullah (HASA) and Clinical Training Centre, Puncak Alam and Sungai Buloh Campuses, Universiti Teknologi MARA, Sungai Buloh, Selangor, Malaysia
| | - Uma Ramaswami
- Royal Free London NHS Foundation Trust, University College London, London, UK
| | - Kausik K Ray
- Imperial Centre for Cardiovascular Disease Prevention, Imperial College London, London, UK
| | - Claudia Stefanutti
- Department of Molecular Medicine, Extracorporeal Therapeutic Techniques Unit, Lipid Clinic and Atherosclerosis Prevention Centre, Regional Centre for Rare Diseases, Immunohematology and Transfusion Medicine, Umberto I Hospital, 'Sapienza' University of Rome, Rome, Italy
| | - Shizuya Yamashita
- Department of Cardiology, Rinku General Medical Center, Osaka, Japan
| | - Jing Pang
- School of Medicine, University of Western Australia, Perth, WA, Australia
| | | | - Raul D Santos
- Lipid Clinic, Heart Institute (InCor), University of São Paulo, São Paulo, Brazil
- Hospital Israelita Albert Einstein, São Paulo, Brazil
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22
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Linder JE, Tao R, Chung WK, Kiryluk K, Liu C, Weng C, Connolly JJ, Hakonarson H, Harr M, Leppig KA, Jarvik GP, Veenstra DL, Aufox S, Chisholm RL, Gordon AS, Hoell C, Rasmussen-Torvik LJ, Smith ME, Holm IA, Miller EM, Prows CA, Elskeally O, Kullo IJ, Lee C, Jose S, Manolio TA, Rowley R, Padi-Adjirackor NA, Wilmayani NK, City B, Wei WQ, Wiesner GL, Rahm AK, Williams JL, Williams MS, Peterson JF. Prospective, multi-site study of healthcare utilization after actionable monogenic findings from clinical sequencing. Am J Hum Genet 2023; 110:1950-1958. [PMID: 37883979 PMCID: PMC10645563 DOI: 10.1016/j.ajhg.2023.10.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 10/05/2023] [Accepted: 10/08/2023] [Indexed: 10/28/2023] Open
Abstract
As large-scale genomic screening becomes increasingly prevalent, understanding the influence of actionable results on healthcare utilization is key to estimating the potential long-term clinical impact. The eMERGE network sequenced individuals for actionable genes in multiple genetic conditions and returned results to individuals, providers, and the electronic health record. Differences in recommended health services (laboratory, imaging, and procedural testing) delivered within 12 months of return were compared among individuals with pathogenic or likely pathogenic (P/LP) findings to matched individuals with negative findings before and after return of results. Of 16,218 adults, 477 unselected individuals were found to have a monogenic risk for arrhythmia (n = 95), breast cancer (n = 96), cardiomyopathy (n = 95), colorectal cancer (n = 105), or familial hypercholesterolemia (n = 86). Individuals with P/LP results more frequently received services after return (43.8%) compared to before return (25.6%) of results and compared to individuals with negative findings (24.9%; p < 0.0001). The annual cost of qualifying healthcare services increased from an average of $162 before return to $343 after return of results among the P/LP group (p < 0.0001); differences in the negative group were non-significant. The mean difference-in-differences was $149 (p < 0.0001), which describes the increased cost within the P/LP group corrected for cost changes in the negative group. When stratified by individual conditions, significant cost differences were observed for arrhythmia, breast cancer, and cardiomyopathy. In conclusion, less than half of individuals received billed health services after monogenic return, which modestly increased healthcare costs for payors in the year following return.
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Affiliation(s)
- Jodell E Linder
- Vanderbilt University Medical Center, Nashville, TN 37203, USA.
| | - Ran Tao
- Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | | | | | - Cong Liu
- Columbia University, New York, NY 10032, USA
| | | | - John J Connolly
- Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Hakon Hakonarson
- Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Margaret Harr
- Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Kathleen A Leppig
- Genetic Services, Kaiser Permanente of Washington, Seattle, WA 98195, USA
| | - Gail P Jarvik
- University of Washington Medical Center, Departments of Medicine (Medical Genetics) and Genome Sciences, Seattle, WA 98195, USA
| | - David L Veenstra
- University of Washington, Department of Pharmacy, Seattle, WA 98195, USA
| | - Sharon Aufox
- Northwestern University, Center for Genetic Medicine, Chicago, IL 60611, USA
| | - Rex L Chisholm
- Northwestern University, Center for Genetic Medicine, Chicago, IL 60611, USA
| | - Adam S Gordon
- Northwestern University, Center for Genetic Medicine, Chicago, IL 60611, USA
| | - Christin Hoell
- Northwestern University, Center for Genetic Medicine, Chicago, IL 60611, USA
| | | | - Maureen E Smith
- Northwestern University, Center for Genetic Medicine, Chicago, IL 60611, USA
| | | | - Erin M Miller
- Division of Cardiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA; Department of Pediatrics, University of Cincinnati, College of Medicine, Cincinnati, OH, USA
| | - Cynthia A Prows
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | | | | | | | - Sheethal Jose
- National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Teri A Manolio
- National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Robb Rowley
- National Human Genome Research Institute, Bethesda, MD 20892, USA
| | | | | | - Brittany City
- Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Wei-Qi Wei
- Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | | | | | - Janet L Williams
- Department of Genomic Health, Geisinger, Danville, PA 17822, USA
| | - Marc S Williams
- Department of Genomic Health, Geisinger, Danville, PA 17822, USA
| | - Josh F Peterson
- Vanderbilt University Medical Center, Nashville, TN 37203, USA
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23
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Abstract
Rare diseases are a leading cause of infant mortality and lifelong disability. To improve outcomes, timely diagnosis and effective treatments are needed. Genomic sequencing has transformed the traditional diagnostic process, providing rapid, accurate and cost-effective genetic diagnoses to many. Incorporating genomic sequencing into newborn screening programmes at the population scale holds the promise of substantially expanding the early detection of treatable rare diseases, with stored genomic data potentially benefitting health over a lifetime and supporting further research. As several large-scale newborn genomic screening projects launch internationally, we review the challenges and opportunities presented, particularly the need to generate evidence of benefit and to address the ethical, legal and psychosocial issues that genomic newborn screening raises.
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Affiliation(s)
- Zornitza Stark
- Australian Genomics, Melbourne, Victoria, Australia.
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.
- Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia.
| | - Richard H Scott
- Great Ormond Street Hospital for Children, London, UK
- UCL Great Ormond Street Institute of Child Health, London, UK
- Genomics England, London, UK
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24
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Dickey L, Gronowski B, Jones K, Rinaldi JB, Emery K, Clemens J, Gordon O, Vartanian K. Participation in genetic screening: testing different outreach methods across a diverse hospital system based patient population. Front Genet 2023; 14:1272931. [PMID: 37900185 PMCID: PMC10602775 DOI: 10.3389/fgene.2023.1272931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 09/29/2023] [Indexed: 10/31/2023] Open
Abstract
Introduction: Genomics has the potential to transform medicine by identifying genetic risk factors that predispose people to certain illnesses. Use of genetic screening is rapidly expanding and shifting towards screening all patients regardless of known risk factors, but research is limited on the success of broad population-level outreach for genetic testing and the effectiveness of different outreach methods across diverse populations. In this study, we tested the effectiveness of Digital Only (emailing and texting) and Brochure Plus Digital (mailed brochure, emailing, and texting) outreach to encourage a diverse patient population to participate in a large hospital system's whole genome sequencing program. Methods: Disproportionate stratified sampling was used to create a study population more demographically diverse than the eligible population and response rates were analyzed overall and by demographics to understand the effectiveness of different outreach strategies. Results: 7.5% of all eligible patients enrolled in the program. While approximately 70% of patients invited to complete genetic testing identified in their EHR as being Hispanic, Black or African America, Asian, or another non-White race, these patients generally enrolled at lower rates than the overall population. Other underrepresented groups had higher enrollment rates including people with Medicaid coverage (8.7%) and those residing in rural areas (10.6%). We found no significant difference in enrollment rates between our Digital-Only and our Brochure Plus Digital outreach approaches in the overall population, but enrollment rates were significantly higher for Asian patients and patients who resided in rural areas in the Brochure Plus Digital group. Across both outreach approaches, links provided in emails were most commonly used for enrollment. Discussion: Our study reveals expected enrollment rates for proactive outreach by a hospital system for genetic testing in a diverse population. As more hospital systems are adopting population-scale genetic testing, these findings can inform future outreach efforts to recruit patients for genetic testing including those patients traditionally underrepresented in genomics.
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Affiliation(s)
- Lindsay Dickey
- Center for Outcomes Research and Education, Portland, OR, United States
| | - Ben Gronowski
- Center for Outcomes Research and Education, Portland, OR, United States
| | - Kyle Jones
- Center for Outcomes Research and Education, Portland, OR, United States
| | - J. B. Rinaldi
- Center for Outcomes Research and Education, Portland, OR, United States
| | - Kate Emery
- Center for Clinical Genetics and Genomics for Providence Southern California, Burbank, CA, United States
| | - Jon Clemens
- Center for Clinical Genetics and Genomics for Providence Southern California, Burbank, CA, United States
| | - Ora Gordon
- Center for Clinical Genetics and Genomics for Providence Southern California, Burbank, CA, United States
| | - Keri Vartanian
- Center for Outcomes Research and Education, Portland, OR, United States
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25
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Savatt JM, Johns A, Schwartz MLB, McDonald WS, Salvati ZM, Oritz NM, Masnick M, Hatchell K, Hao J, Buchanan AH, Williams MS. Testing and Management of Iron Overload After Genetic Screening-Identified Hemochromatosis. JAMA Netw Open 2023; 6:e2338995. [PMID: 37870835 PMCID: PMC10594145 DOI: 10.1001/jamanetworkopen.2023.38995] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 09/08/2023] [Indexed: 10/24/2023] Open
Abstract
Importance HFE gene-associated hereditary hemochromatosis type 1 (HH1) is underdiagnosed, resulting in missed opportunities for preventing morbidity and mortality. Objective To assess whether screening for p.Cys282Tyr homozygosity is associated with recognition and management of asymptomatic iron overload. Design, Setting, and Participants This cross-sectional study obtained data from the Geisinger MyCode Community Health Initiative, a biobank of biological samples and linked electronic health record data from a rural, integrated health care system. Participants included those who received a p.Cys282Tyr homozygous result via genomic screening (MyCode identified), had previously diagnosed HH1 (clinically identified), and those negative for p.Cys282Tyr homozygosity between 2017 and 2018. Data were analyzed from April 2020 to August 2023. Exposure Disclosure of a p.Cys282Tyr homozygous result. Main Outcomes and Measures Postdisclosure management and HFE-associated phenotypes in MyCode-identified participants were analyzed. Rates of HFE-associated phenotypes in MyCode-identified participants were compared with those of clinically identified participants. Relevant laboratory values and rates of laboratory iron overload among participants negative for p.Cys282Tyr homozygosity were compared with those of MyCode-identified participants. Results A total of 86 601 participants had available exome sequences at the time of analysis, of whom 52 994 (61.4%) were assigned female at birth, and the median (IQR) age was 62.0 (47.0-73.0) years. HFE p.Cys282Tyr homozygosity was disclosed to 201 participants, of whom 57 (28.4%) had a prior clinical HH1 diagnosis, leaving 144 participants who learned of their status through screening. There were 86 300 individuals negative for p.Cys282Tyr homozygosity. After result disclosure, among MyCode-identified participants, 99 (68.8%) had a recommended laboratory test and 36 (69.2%) with laboratory or liver biopsy evidence of iron overload began phlebotomy or chelation. Fifty-three (36.8%) had iron overload; rates of laboratory iron overload were higher in MyCode-identified participants than participants negative for p.Cys282Tyr homozygosity (females: 34.1% vs 2.1%, P < .001; males: 39.0% vs 2.9%, P < .001). Iron overload (females: 34.1% vs 79.3%, P < .001; males: 40.7% vs 67.9%, P = .02) and some liver-associated phenotypes were observed at lower frequencies in MyCode-identified participants compared with clinically identified individuals. Conclusions and Relevance Results of this cross-sectional study showed the ability of genomic screening to identify undiagnosed iron overload and encourage relevant management, suggesting the potential benefit of population screening for HFE p.Cys282Tyr homozygosity. Further studies are needed to examine the implications of genomic screening for health outcomes and cost-effectiveness.
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Affiliation(s)
| | - Alicia Johns
- Department of Population Health Sciences, Geisinger, Danville, Pennsylvania
| | - Marci L. B. Schwartz
- Ted Rogers Centre for Heart Research, Cardiac Genome Clinic, The Hospital for Sick Children, Toronto, Ontario, Canada
- Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, Ontario, Canada
| | | | | | - Nicole M. Oritz
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
| | - Max Masnick
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
| | | | - Jing Hao
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
- Department of Population Health Sciences, Geisinger, Danville, Pennsylvania
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Cannon A, McMillan O, Kelley WV, East KM, Cochran ME, Miskell EL, Moss IP, Garner-Duckworth S, Redden DT, Might M, Barsh GS, Korf BR. Medical and psychosocial outcomes of state-funded population genomic screening. Clin Genet 2023; 104:434-442. [PMID: 37340305 PMCID: PMC11299714 DOI: 10.1111/cge.14394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 06/06/2023] [Accepted: 06/09/2023] [Indexed: 06/22/2023]
Abstract
As the uptake of population screening expands, assessment of medical and psychosocial outcomes is needed. Through the Alabama Genomic Health Initiative (AGHI), a state-funded genomic research program, individuals received screening for pathogenic or likely pathogenic variants in 59 actionable genes via genotyping. Of the 3874 eligible participants that received screening results, 858 (22%) responded to an outcomes survey. The most commonly reported motivation for seeking testing through AGHI was contribution to genetic research (64%). Participants with positive results reported a higher median number of planned actions (median = 5) due to AGHI results as compared to negative results (median = 3). Interviews were conducted with survey participants with positive screening results. As determined by certified genetic counselors, 50% of interviewees took appropriate medical action based on their result. There were no negative or harmful actions taken. These findings indicate population genomic screening of an unselected adult population is feasible, is not harmful, and may have positive outcomes on participants now and in the future; however, further research is needed in order to assess clinical utility.
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Affiliation(s)
- Ashley Cannon
- Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Olivia McMillan
- School of Health Professions, University of Alabama at Birmingham, Birmingham, AL, USA
| | | | - Kelly M East
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | | | - Edrika L. Miskell
- Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Irene P Moss
- Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | | | - David T Redden
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Matthew Might
- Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Gregory S Barsh
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Bruce R Korf
- Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
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27
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Guo B, Knerr S, Kauffman TL, Mittendorf KF, Keast E, Gilmore MJ, Feigelson HS, Lynch FL, Muessig KR, Okuyama S, Zepp JM, Veenstra DL, Hsu L, Phipps AI, Lindström S, Leo MC, Goddard KAB, Wilfond BS, Devine B. Risk management actions following genetic testing in the Cancer Health Assessments Reaching Many (CHARM) Study: A prospective cohort study. Cancer Med 2023; 12:19112-19125. [PMID: 37644850 PMCID: PMC10557878 DOI: 10.1002/cam4.6485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 08/07/2023] [Accepted: 08/18/2023] [Indexed: 08/31/2023] Open
Abstract
BACKGROUND Genetic testing can identify cancer risk early, enabling prevention and early detection. We describe use of risk management interventions following genetic testing in the Cancer Health Assessment Reaching Many (CHARM) study. CHARM assessed risk and provided genetic testing to low income, low literacy, and other underserved populations that historically face barriers to accessing cancer genetic services. METHODS CHARM was implemented in Kaiser Permanente Northwest (KPNW) and Denver Health (DH) between 2018 and 2020. We identified post-testing screening (mammography, breast MRI, colonoscopy) and surgical (mastectomy, oophorectomy) procedures using electronic health records. We examined utilization in participants who did and did not receive actionable risk management recommendations from study genetic counselors following national guidelines. RESULTS CHARM participants were followed for an average of 15.4 months (range: 0.4-27.8 months) after results disclosure. Less than 2% (11/680) received actionable risk management recommendations (i.e., could be completed in the initial years following testing) based on their test result. Among those who received actionable recommendations, risk management utilization was moderate (54.5%, 6/11 completed any procedure) and varied by procedure (mammogram: 0/3; MRI: 2/4; colonoscopy: 4/5; mastectomy: 1/5; oophorectomy: 0/3). Cancer screening and surgery procedures were rare in participants without actionable recommendations. CONCLUSION Though the number of participants who received actionable risk management recommendations was small, our results suggest that implementing CHARM's risk assessment and testing model increased access to evidence-based genetic services and provided opportunities for patients to engage in recommended preventive care, without encouraging risk management overuse.
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Affiliation(s)
- Boya Guo
- School of Public HealthUniversity of WashingtonSeattleWashingtonUSA
| | - Sarah Knerr
- School of Public HealthUniversity of WashingtonSeattleWashingtonUSA
| | - Tia L. Kauffman
- Center for Health Research, Kaiser Permanente NorthwestPortlandOregonUSA
| | - Kathleen F. Mittendorf
- Vanderbilt‐Ingram Cancer CenterVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Erin Keast
- Center for Health Research, Kaiser Permanente NorthwestPortlandOregonUSA
| | - Marian J. Gilmore
- Department of Translational and Applied GenomicsCenter for Health ResearchPortlandOregonUSA
| | | | - Frances L. Lynch
- Center for Health Research, Kaiser Permanente NorthwestPortlandOregonUSA
| | - Kristin R. Muessig
- Department of Translational and Applied GenomicsCenter for Health ResearchPortlandOregonUSA
| | - Sonia Okuyama
- Division of Oncology, Denver Health and Hospital AuthorityDenverColoradoUSA
| | - Jamilyn M. Zepp
- Department of Translational and Applied GenomicsCenter for Health ResearchPortlandOregonUSA
| | - David L. Veenstra
- The Comparative Health Outcomes, Policy, and Economics (CHOICE) Institute, School of PharmacyUniversity of WashingtonSeattleWashingtonUSA
| | - Li Hsu
- School of Public HealthUniversity of WashingtonSeattleWashingtonUSA
- Division of Public Health SciencesFred Hutchinson Cancer CenterSeattleWashingtonUSA
| | - Amanda I. Phipps
- School of Public HealthUniversity of WashingtonSeattleWashingtonUSA
- Division of Public Health SciencesFred Hutchinson Cancer CenterSeattleWashingtonUSA
| | - Sara Lindström
- School of Public HealthUniversity of WashingtonSeattleWashingtonUSA
- Division of Public Health SciencesFred Hutchinson Cancer CenterSeattleWashingtonUSA
| | - Michael C. Leo
- Center for Health Research, Kaiser Permanente NorthwestPortlandOregonUSA
| | - Katrina A. B. Goddard
- Department of Translational and Applied GenomicsCenter for Health ResearchPortlandOregonUSA
| | - Benjamin S. Wilfond
- Treuman Katz Center for Pediatric BioethicsSeattle Children's Research InstituteSeattleWashingtonUSA
- Department of Pediatrics, Division of Bioethics and Palliative CareUniversity of WashingtonSeattleWashingtonUSA
| | - Beth Devine
- School of Public HealthUniversity of WashingtonSeattleWashingtonUSA
- The Comparative Health Outcomes, Policy, and Economics (CHOICE) Institute, School of PharmacyUniversity of WashingtonSeattleWashingtonUSA
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28
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Kodida R, Reble E, Clausen M, Shickh S, Mighton C, Sam J, Forster N, Panchal S, Aronson M, Semotiuk K, Graham T, Silberman Y, Randall Armel S, McCuaig JM, Cohn I, Morel CF, Elser C, Eisen A, Carroll JC, Glogowski E, Schrader KA, Di Gioacchino V, Lerner-Ellis J, Kim RH, Bombard Y. A model for the return and referral of all clinically significant secondary findings of genomic sequencing. J Med Genet 2023; 60:733-739. [PMID: 37217257 DOI: 10.1136/jmg-2022-109091] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 04/19/2023] [Indexed: 05/24/2023]
Abstract
Secondary findings (SFs) identified through genomic sequencing (GS) can offer a wide range of health benefits to patients. Resource and capacity constraints pose a challenge to their clinical management; therefore, clinical workflows are needed to optimise the health benefits of SFs. In this paper, we describe a model we created for the return and referral of all clinically significant SFs, beyond medically actionable results, from GS. As part of a randomised controlled trial evaluating the outcomes and costs of disclosing all clinically significant SFs from GS, we consulted genetics and primary care experts to determine a feasible workflow to manage SFs. Consensus was sought to determine appropriate clinical recommendations for each category of SF and which clinician specialist would provide follow-up care. We developed a communication and referral plan for each category of SFs. This involved referrals to specialised clinics, such as an Adult Genetics clinic, for highly penetrant medically actionable findings. Common and non-urgent SFs, such as pharmacogenomics and carrier status results for non-family planning participants, were directed back to the family physician (FP). SF results and recommendations were communicated directly to participants to respect autonomy and to their FPs to support follow-up of SFs. We describe a model for the return and referral of all clinically significant SFs to facilitate the utility of GS and promote the health benefits of SFs. This may serve as a model for others returning GS results transitioning participants from research to clinical settings.
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Affiliation(s)
- Rita Kodida
- Genomics Health Services & Policy Research Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Emma Reble
- Genomics Health Services & Policy Research Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Marc Clausen
- Genomics Health Services & Policy Research Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Salma Shickh
- Genomics Health Services & Policy Research Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
- Institute of Health Policy, Management & Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Chloe Mighton
- Genomics Health Services & Policy Research Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
- Institute of Health Policy, Management & Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Jordan Sam
- Genomics Health Services & Policy Research Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Nicole Forster
- Fred A. Litwin Family Centre in Genetic Medicine, University Health Network, Toronto, Ontario, Canada
| | - Seema Panchal
- The Marvelle Koffler Breast Centre, Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Melyssa Aronson
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Zane Cohen Centre for Digestive Diseases, Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada
| | - Kara Semotiuk
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Zane Cohen Centre for Digestive Diseases, Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada
| | - Tracy Graham
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Yael Silberman
- Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Susan Randall Armel
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Division of Medical Oncology & Hematology, Princess Margaret Hospital Cancer Centre, Toronto, Ontario, Canada
| | - Jeanna M McCuaig
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Division of Medical Oncology & Hematology, Princess Margaret Hospital Cancer Centre, Toronto, Ontario, Canada
| | - Iris Cohn
- Division of Clinical Pharmacology & Toxicology, Hospital for Sick Children, Toronto, Ontario, Canada
| | - Chantal F Morel
- Fred A. Litwin Family Centre in Genetic Medicine, University Health Network, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Christine Elser
- The Marvelle Koffler Breast Centre, Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Andrea Eisen
- Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - June C Carroll
- Department of Family & Community Medicine, University of Toronto, Toronto, Ontario, Canada
- Granovsky Gluskin Family Medicine Centre, Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada
| | | | - Kasmintan A Schrader
- British Columbia Cancer Agency, Vancouver, British Columbia, Canada
- Department of Medical Genetics, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Vanessa Di Gioacchino
- The Marvelle Koffler Breast Centre, Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada
- Pathology & Laboratory Medicine, Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada
| | - Jordan Lerner-Ellis
- Pathology & Laboratory Medicine, Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada
- Lunenfeld Tanenbaum Research Institute, Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada
| | - Raymond H Kim
- Division of Medical Oncology & Hematology, Princess Margaret Hospital Cancer Centre, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Yvonne Bombard
- Genomics Health Services & Policy Research Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
- Institute of Health Policy, Management & Evaluation, University of Toronto, Toronto, Ontario, Canada
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29
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Kurian AW, Abrahamse P, Furgal A, Ward KC, Hamilton AS, Hodan R, Tocco R, Liu L, Berek JS, Hoang L, Yussuf A, Susswein L, Esplin ED, Slavin TP, Gomez SL, Hofer TP, Katz SJ. Germline Genetic Testing After Cancer Diagnosis. JAMA 2023; 330:43-51. [PMID: 37276540 PMCID: PMC10242510 DOI: 10.1001/jama.2023.9526] [Citation(s) in RCA: 31] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 05/18/2023] [Indexed: 06/07/2023]
Abstract
Importance Germline genetic testing is recommended by practice guidelines for patients diagnosed with cancer to enable genetically targeted treatment and identify relatives who may benefit from personalized cancer screening and prevention. Objective To describe the prevalence of germline genetic testing among patients diagnosed with cancer in California and Georgia between 2013 and 2019. Design, Setting, and Participants Observational study including patients aged 20 years or older who had been diagnosed with any type of cancer between January 1, 2013, and March 31, 2019, that was reported to statewide Surveillance, Epidemiology, and End Results registries in California and Georgia. These patients were linked to genetic testing results from 4 laboratories that performed most germline testing for California and Georgia. Main Outcomes and Measures The primary outcome was germline genetic testing within 2 years of a cancer diagnosis. Testing trends were analyzed with logistic regression modeling. The results of sequencing each gene, including variants associated with increased cancer risk (pathogenic results) and variants whose cancer risk association was unknown (uncertain results), were evaluated. The genes were categorized according to their primary cancer association, including breast or ovarian, gastrointestinal, and other, and whether practice guidelines recommended germline testing. Results Among 1 369 602 patients diagnosed with cancer between 2013 and 2019 in California and Georgia, 93 052 (6.8%) underwent germline testing through March 31, 2021. The proportion of patients tested varied by cancer type: male breast (50%), ovarian (38.6%), female breast (26%), multiple (7.5%), endometrial (6.4%), pancreatic (5.6%), colorectal (5.6%), prostate (1.1%), and lung (0.3%). In a logistic regression model, compared with the 31% (95% CI, 30%-31%) of non-Hispanic White patients with male breast cancer, female breast cancer, or ovarian cancer who underwent testing, patients of other races and ethnicities underwent testing less often: 22% (95% CI, 21%-22%) of Asian patients, 25% (95% CI, 24%-25%) of Black patients, and 23% (95% CI, 23%-23%) of Hispanic patients (P < .001 using the χ2 test). Of all pathogenic results, 67.5% to 94.9% of variants were identified in genes for which practice guidelines recommend testing and 68.3% to 83.8% of variants were identified in genes associated with the diagnosed cancer type. Conclusions and Relevance Among patients diagnosed with cancer in California and Georgia between 2013 and 2019, only 6.8% underwent germline genetic testing. Compared with non-Hispanic White patients, rates of testing were lower among Asian, Black, and Hispanic patients.
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Affiliation(s)
- Allison W. Kurian
- Department of Medicine, School of Medicine, Stanford University, Stanford, California
- Department of Epidemiology and Population Health, School of Medicine, Stanford University, Stanford, California
| | - Paul Abrahamse
- Department of Health Management and Policy, School of Public Health, University of Michigan, Ann Arbor
| | - Allison Furgal
- Department of Health Management and Policy, School of Public Health, University of Michigan, Ann Arbor
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
| | - Kevin C. Ward
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia
| | - Ann S. Hamilton
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles
| | - Rachel Hodan
- Department of Pediatrics, School of Medicine, Stanford University, Stanford, California
| | - Rachel Tocco
- Department of Health Management and Policy, School of Public Health, University of Michigan, Ann Arbor
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
| | - Lihua Liu
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles
| | - Jonathan S. Berek
- Department of Obstetrics and Gynecology, School of Medicine, Stanford University, Stanford, California
| | | | | | | | | | | | - Scarlett L. Gomez
- Department of Epidemiology and Biostatistics, University of California, San Francisco
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco
| | - Timothy P. Hofer
- Department of Internal Medicine, Michigan Medicine, University of Michigan, Ann Arbor
- Center for Clinical Management Research, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, Michigan
| | - Steven J. Katz
- Department of Health Management and Policy, School of Public Health, University of Michigan, Ann Arbor
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
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30
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Guzauskas GF, Garbett S, Zhou Z, Schildcrout JS, Graves JA, Williams MS, Hao J, Jones LK, Spencer SJ, Jiang S, Veenstra DL, Peterson JF. Population Genomic Screening for Three Common Hereditary Conditions : A Cost-Effectiveness Analysis. Ann Intern Med 2023; 176:585-595. [PMID: 37155986 DOI: 10.7326/m22-0846] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/10/2023] Open
Abstract
BACKGROUND The cost-effectiveness of screening the U.S. population for Centers for Disease Control and Prevention (CDC) Tier 1 genomic conditions is unknown. OBJECTIVE To estimate the cost-effectiveness of simultaneous genomic screening for Lynch syndrome (LS), hereditary breast and ovarian cancer syndrome (HBOC), and familial hypercholesterolemia (FH). DESIGN Decision analytic Markov model. DATA SOURCES Published literature. TARGET POPULATION Separate age-based cohorts (ages 20 to 60 years at time of screening) of racially and ethnically representative U.S. adults. TIME HORIZON Lifetime. PERSPECTIVE U.S. health care payer. INTERVENTION Population genomic screening using clinical sequencing with a restricted panel of high-evidence genes, cascade testing of first-degree relatives, and recommended preventive interventions for identified probands. OUTCOME MEASURES Incident breast, ovarian, and colorectal cancer cases; incident cardiovascular events; quality-adjusted survival; and costs. RESULTS OF BASE-CASE ANALYSIS Screening 100 000 unselected 30-year-olds resulted in 101 (95% uncertainty interval [UI], 77 to 127) fewer overall cancer cases and 15 (95% UI, 4 to 28) fewer cardiovascular events and an increase of 495 quality-adjusted life-years (QALYs) (95% UI, 401 to 757) at an incremental cost of $33.9 million (95% UI, $27.0 million to $41.1 million). The incremental cost-effectiveness ratio was $68 600 per QALY gained (95% UI, $41 800 to $88 900). RESULTS OF SENSITIVITY ANALYSIS Screening 30-, 40-, and 50-year-old cohorts was cost-effective in 99%, 88%, and 19% of probabilistic simulations, respectively, at a $100 000-per-QALY threshold. The test costs at which screening 30-, 40-, and 50-year-olds reached the $100 000-per-QALY threshold were $413, $290, and $166, respectively. Variant prevalence and adherence to preventive interventions were also highly influential parameters. LIMITATIONS Population averages for model inputs, which were derived predominantly from European populations, vary across ancestries and health care environments. CONCLUSION Population genomic screening with a restricted panel of high-evidence genes associated with 3 CDC Tier 1 conditions is likely to be cost-effective in U.S. adults younger than 40 years if the testing cost is relatively low and probands have access to preventive interventions. PRIMARY FUNDING SOURCE National Human Genome Research Institute.
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Affiliation(s)
- Gregory F Guzauskas
- The CHOICE Institute, Department of Pharmacy, University of Washington, Seattle, Washington (G.F.G., S.J.)
| | - Shawn Garbett
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee (S.G., J.S.S.)
| | - Zilu Zhou
- Department of Health Policy, Vanderbilt University Medical Center, Nashville, Tennessee (Z.Z., J.A.G.)
| | - Jonathan S Schildcrout
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee (S.G., J.S.S.)
| | - John A Graves
- Department of Health Policy, Vanderbilt University Medical Center, Nashville, Tennessee (Z.Z., J.A.G.)
| | - Marc S Williams
- Department of Genomic Health, Geisinger, Danville, Pennsylvania (M.S.W.)
| | - Jing Hao
- Department of Genomic Health and Department of Population Health Sciences, Geisinger, Danville, Pennsylvania (J.H.)
| | - Laney K Jones
- Department of Population Health Sciences and Heart Institute, Geisinger, Danville, Pennsylvania (L.K.J.)
| | - Scott J Spencer
- Institute for Public Health Genetics, University of Washington, Seattle, Washington (S.J.S.)
| | - Shangqing Jiang
- The CHOICE Institute, Department of Pharmacy, University of Washington, Seattle, Washington (G.F.G., S.J.)
| | - David L Veenstra
- The CHOICE Institute, Department of Pharmacy, and Institute for Public Health Genetics, University of Washington, Seattle, Washington (D.L.V.)
| | - Josh F Peterson
- Department of Biomedical Informatics and Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee (J.F.P.)
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31
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Rao ND, Kaganovsky J, Malouf EA, Coe S, Huey J, Tsinajinne D, Hassan S, King KM, Fullerton SM, Chen AT, Shirts BH. Diagnostic yield of genetic screening in a diverse, community-ascertained cohort. Genome Med 2023; 15:26. [PMID: 37069702 PMCID: PMC10111761 DOI: 10.1186/s13073-023-01174-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 03/16/2023] [Indexed: 04/19/2023] Open
Abstract
BACKGROUND Population screening for genetic risk of adult-onset preventable conditions has been proposed as an attractive public health intervention. Screening unselected individuals can identify many individuals who will not be identified through current genetic testing guidelines. METHODS We sought to evaluate enrollment in and diagnostic yield of population genetic screening in a resource-limited setting among a diverse population. We developed a low-cost, short-read next-generation sequencing panel of 25 genes that had 98.4% sensitivity and 99.98% specificity compared to diagnostic panels. We used email invitations to recruit a diverse cohort of patients in the University of Washington Medical Center system unselected for personal or family history of hereditary disease. Participants were sent a saliva collection kit in the mail with instructions on kit use and return. Results were returned using a secure online portal. Enrollment and diagnostic yield were assessed overall and across race and ethnicity groups. RESULTS Overall, 40,857 people were invited and 2889 (7.1%) enrolled. Enrollment varied across race and ethnicity groups, with the lowest enrollment among African American individuals (3.3%) and the highest among Multiracial or Other Race individuals (13.0%). Of 2864 enrollees who received screening results, 106 actionable variants were identified in 103 individuals (3.6%). Of those who screened positive, 30.1% already knew about their results from prior genetic testing. The diagnostic yield was 74 new, actionable genetic findings (2.6%). The addition of more recently identified cancer risk genes increased the diagnostic yield of screening. CONCLUSIONS Population screening can identify additional individuals that could benefit from prevention, but challenges in recruitment and sample collection will reduce actual enrollment and yield. These challenges should not be overlooked in intervention planning or in cost and benefit analysis.
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Affiliation(s)
- Nandana D Rao
- Institute for Public Health Genetics, University of Washington, Seattle, WA, USA
| | - Jailanie Kaganovsky
- Department of Laboratory Medicine and Pathology, University of Washington, Rm NW120, Box 357110 1959 NE Pacific Street, WA, 98195, Seattle, USA
| | - Emily A Malouf
- Department of Laboratory Medicine and Pathology, University of Washington, Rm NW120, Box 357110 1959 NE Pacific Street, WA, 98195, Seattle, USA
| | - Sandy Coe
- Department of Laboratory Medicine and Pathology, University of Washington, Rm NW120, Box 357110 1959 NE Pacific Street, WA, 98195, Seattle, USA
| | - Jennifer Huey
- Department of Laboratory Medicine and Pathology, University of Washington, Rm NW120, Box 357110 1959 NE Pacific Street, WA, 98195, Seattle, USA
| | - Darwin Tsinajinne
- Department of Laboratory Medicine and Pathology, University of Washington, Rm NW120, Box 357110 1959 NE Pacific Street, WA, 98195, Seattle, USA
| | - Sajida Hassan
- Department of Laboratory Medicine and Pathology, University of Washington, Rm NW120, Box 357110 1959 NE Pacific Street, WA, 98195, Seattle, USA
| | - Kristine M King
- Institute for Public Health Genetics, University of Washington, Seattle, WA, USA
| | - Stephanie M Fullerton
- Department of Bioethics & Humanities, University of Washington School of Medicine, Seattle, WA, USA
| | - Annie T Chen
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA
| | - Brian H Shirts
- Department of Laboratory Medicine and Pathology, University of Washington, Rm NW120, Box 357110 1959 NE Pacific Street, WA, 98195, Seattle, USA.
- Brotman Baty Institute, Seattle, WA, USA.
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Dikilitas O, Sherafati A, Saadatagah S, Satterfield BA, Kochan DC, Anderson KC, Chung WK, Hebbring SJ, Salvati ZM, Sharp RR, Sturm AC, Gibbs RA, Rowley R, Venner E, Linder JE, Jones LK, Perez EF, Peterson JF, Jarvik GP, Rehm HL, Zouk H, Roden DM, Williams MS, Manolio TA, Kullo IJ. Familial Hypercholesterolemia in the Electronic Medical Records and Genomics Network: Prevalence, Penetrance, Cardiovascular Risk, and Outcomes After Return of Results. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2023; 16:e003816. [PMID: 37071725 PMCID: PMC10113961 DOI: 10.1161/circgen.122.003816] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 01/03/2023] [Indexed: 02/24/2023]
Abstract
BACKGROUND The implications of secondary findings detected in large-scale sequencing projects remain uncertain. We assessed prevalence and penetrance of pathogenic familial hypercholesterolemia (FH) variants, their association with coronary heart disease (CHD), and 1-year outcomes following return of results in phase III of the electronic medical records and genomics network. METHODS Adult participants (n=18 544) at 7 sites were enrolled in a prospective cohort study to assess the clinical impact of returning results from targeted sequencing of 68 actionable genes, including LDLR, APOB, and PCSK9. FH variant prevalence and penetrance (defined as low-density lipoprotein cholesterol >155 mg/dL) were estimated after excluding participants enrolled on the basis of hypercholesterolemia. Multivariable logistic regression was used to estimate the odds of CHD compared to age- and sex-matched controls without FH-associated variants. Process (eg, referral to a specialist or ordering new tests), intermediate (eg, new diagnosis of FH), and clinical (eg, treatment modification) outcomes within 1 year after return of results were ascertained by electronic health record review. RESULTS The prevalence of FH-associated pathogenic variants was 1 in 188 (69 of 13,019 unselected participants). Penetrance was 87.5%. The presence of an FH variant was associated with CHD (odds ratio, 3.02 [2.00-4.53]) and premature CHD (odds ratio, 3.68 [2.34-5.78]). At least 1 outcome occurred in 92% of participants; 44% received a new diagnosis of FH and 26% had treatment modified following return of results. CONCLUSIONS In a multisite cohort of electronic health record-linked biobanks, monogenic FH was prevalent, penetrant, and associated with presence of CHD. Nearly half of participants with an FH-associated variant received a new diagnosis of FH and a quarter had treatment modified after return of results. These results highlight the potential utility of sequencing electronic health record-linked biobanks to detect FH.
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Affiliation(s)
- Ozan Dikilitas
- Department of Internal Medicine (O.D.), Mayo Clinic, Rochester, MN
- Department of Cardiovascular Medicine (O.D., A.S., S.S., B.A.S., D.C.K., I.J.K.), Mayo Clinic, Rochester, MN
| | - Alborz Sherafati
- Department of Cardiovascular Medicine (O.D., A.S., S.S., B.A.S., D.C.K., I.J.K.), Mayo Clinic, Rochester, MN
| | - Seyedmohammad Saadatagah
- Department of Cardiovascular Medicine (O.D., A.S., S.S., B.A.S., D.C.K., I.J.K.), Mayo Clinic, Rochester, MN
| | - Benjamin A Satterfield
- Department of Cardiovascular Medicine (O.D., A.S., S.S., B.A.S., D.C.K., I.J.K.), Mayo Clinic, Rochester, MN
| | - David C Kochan
- Department of Cardiovascular Medicine (O.D., A.S., S.S., B.A.S., D.C.K., I.J.K.), Mayo Clinic, Rochester, MN
| | - Katherine C Anderson
- Department of Medicine (K.C.A., J.E.L., J.F.P.), Vanderbilt University Medical Center, Nashville, TN
| | - Wendy K Chung
- Departments of Pediatrics and Medicine, Columbia University Irving Medical Center, New York (W.K.C.)
| | | | - Zachary M Salvati
- Genomic Medicine Institute, Geisinger, Danville, PA (Z.M.S., A.C.S., L.K.J., M.S.W.)
| | - Richard R Sharp
- Biomedical Ethics Research Program (R.R.S.), Mayo Clinic, Rochester, MN
| | - Amy C Sturm
- Genomic Medicine Institute, Geisinger, Danville, PA (Z.M.S., A.C.S., L.K.J., M.S.W.)
| | - Richard A Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX (R.A.G., E.V.)
| | - Robb Rowley
- National Human Genome Research Institute, Bethesda, MD (R.R., T.A.M.)
| | - Eric Venner
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX (R.A.G., E.V.)
| | - Jodell E Linder
- Department of Medicine (K.C.A., J.E.L., J.F.P.), Vanderbilt University Medical Center, Nashville, TN
| | - Laney K Jones
- Genomic Medicine Institute, Geisinger, Danville, PA (Z.M.S., A.C.S., L.K.J., M.S.W.)
| | - Emma F Perez
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, MA (E.F.P.)
| | - Josh F Peterson
- Department of Medicine (K.C.A., J.E.L., J.F.P.), Vanderbilt University Medical Center, Nashville, TN
| | - Gail P Jarvik
- Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington Medical Center, Seattle (G.P.J.)
| | - Heidi L Rehm
- Laboratory for Molecular Medicine, Partners Healthcare Personalized Medicine, Cambridge (H.L.R., H.Z.)
| | - Hana Zouk
- Laboratory for Molecular Medicine, Partners Healthcare Personalized Medicine, Cambridge (H.L.R., H.Z.)
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston (H.Z.)
| | - Dan M Roden
- Departments of Medicine, Pharmacology, and Biomedical Informatics (D.M.R.), Vanderbilt University Medical Center, Nashville, TN
| | - Marc S Williams
- Genomic Medicine Institute, Geisinger, Danville, PA (Z.M.S., A.C.S., L.K.J., M.S.W.)
| | - Teri A Manolio
- National Human Genome Research Institute, Bethesda, MD (R.R., T.A.M.)
| | - Iftikhar J Kullo
- Department of Cardiovascular Medicine (O.D., A.S., S.S., B.A.S., D.C.K., I.J.K.), Mayo Clinic, Rochester, MN
- Gonda Vascular Ctr (I.J.K.), Mayo Clinic, Rochester, MN
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Etchegary H, Pike A, Puddester R, Watkins K, Warren M, Francis V, Woods M, Green J, Savas S, Seal M, Gao Z, Avery S, Curtis F, McGrath J, MacDonald D, Burry TN, Dawson L. Cancer prevention in cancer predisposition syndromes: A protocol for testing the feasibility of building a hereditary cancer research registry and nurse navigator follow up model. PLoS One 2022; 17:e0279317. [PMID: 36548287 PMCID: PMC9778977 DOI: 10.1371/journal.pone.0279317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 12/02/2022] [Indexed: 12/24/2022] Open
Abstract
Monogenic, high penetrance syndromes, conferring an increased risk of malignancies in multiple organs, are important contributors to the hereditary burden of cancer. Early detection and risk reduction strategies in patients with a cancer predisposition syndrome can save their lives. However, despite evidence supporting the benefits of early detection and risk reduction strategies, most Canadian jurisdictions have not implemented programmatic follow up of these patients. In our study site in the province of Newfoundland and Labrador (NL), Canada, there is no centralized, provincial registry of high-risk individuals. There is no continuity or coordination of care providing cancer genetics expertise and no process to ensure that patients are referred to the appropriate specialists or risk management interventions. This paper describes a study protocol to test the feasibility of obtaining and analyzing patient risk management data, specifically patients affected by hereditary breast ovarian cancer syndrome (HBOC; BRCA 1 and BRCA 2 genes) and Lynch syndrome (LS; MLH1, MSH2, MSH6, and PMS2 genes). Through a retrospective cohort study, we will describe these patients' adherence to risk management guidelines and test its relationship to health outcomes, including cancer incidence and stage. Through a qualitative interviews, we will determine the priorities and preferences of patients with any inherited cancer mutation for a follow up navigation model of risk management. Study data will inform a subsequent funding application focused on creating and evaluating a research registry and follow up nurse navigation model. It is not currently known what proportion of cancer mutation carriers are receiving care according to guidelines. Data collected in this study will provide clinical uptake and health outcome information so gaps in care can be identified. Data will also provide patient preference information to inform ongoing and planned research with cancer mutation carriers.
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Affiliation(s)
- Holly Etchegary
- Clinical Epidemiology, Faculty of Medicine, Memorial University of Newfoundland, St. John’s, Newfoundland, Canada
- * E-mail:
| | - April Pike
- Faculty of Nursing, Memorial University of Newfoundland, St. John’s, Newfoundland, Canada
| | - Rebecca Puddester
- Faculty of Nursing, Memorial University of Newfoundland, St. John’s, Newfoundland, Canada
| | - Kathy Watkins
- Centre for Nursing and Health Studies, Eastern Health, St. John’s, Newfoundland, Canada
| | - Mike Warren
- Patient Partner, Faculty of Medicine, Memorial University of Newfoundland, St. John’s, Newfoundland, Canada
| | - Vanessa Francis
- Patient Partner, Faculty of Medicine, Memorial University of Newfoundland, St. John’s, Newfoundland, Canada
| | - Michael Woods
- Division of Biomedical Sciences, Discipline of Oncology, Faculty of Medicine, Memorial University of Newfoundland, St. John’s, Newfoundland, Canada
| | - Jane Green
- Division of Biomedical Sciences, Discipline of Oncology, Faculty of Medicine, Memorial University of Newfoundland, St. John’s, Newfoundland, Canada
| | - Sevtap Savas
- Division of Biomedical Sciences, Discipline of Oncology, Faculty of Medicine, Memorial University of Newfoundland, St. John’s, Newfoundland, Canada
| | - Melanie Seal
- Discipline of Oncology, Faculty of Medicine, Memorial University of Newfoundland, Cancer Care Program, Eastern Health, St. John’s, Newfoundland, Canada
| | - Zhiwei Gao
- Clinical Epidemiology, Faculty of Medicine, Memorial University of Newfoundland, St. John’s, Newfoundland, Canada
| | - Susan Avery
- Family Medicine, Faculty of Medicine, Memorial University of Newfoundland, St. John’s, Newfoundland, Canada
| | - Fiona Curtis
- Provincial Medical Genetics Program, Eastern Health, St. John’s, Newfoundland, Canada
| | - Jerry McGrath
- Gastroenterology, Faculty of Medicine, Memorial University of Newfoundland, St. John’s, Newfoundland, Canada
| | - Donald MacDonald
- Newfoundland and Labrador Centre for Health Information, St. John’s, Newfoundland, Canada
| | - T. Nadine Burry
- Clinical Epidemiology, Faculty of Medicine, Memorial University of Newfoundland, St. John’s, Newfoundland, Canada
| | - Lesa Dawson
- Obstetrics and Gynecology, Faculty of Medicine, Memorial University of Newfoundland, St. John’s, Newfoundland, Canada
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Tiller JM, Bakshi A, Brotchie AR, Green RC, Winship IM, Lacaze P. Public willingness to participate in population DNA screening in Australia. J Med Genet 2022:jmg-2022-108921. [DOI: 10.1136/jmg-2022-108921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Accepted: 11/01/2022] [Indexed: 12/02/2022]
Abstract
BackgroundPopulation-based DNA screening for medically actionable conditions has the potential to improve public health by enabling early detection, treatment and/or prevention; however, public attitudes and willingness to participate in DNA screening have not been well investigated.MethodsWe presented a scenario to members of the Australian public, randomly selected from the electoral roll via the Australian Survey of Societal Attitudes, describing an adult population DNA screening programme currently under development, to detect risk of medically actionable cancers and heart disease. We asked questions regarding willingness to participate and pay, preferred delivery methods and concerns.ResultsWe received 1060 completed questionnaires (response rate 23%, mean age 58 years). The vast majority (>92%) expressed willingness to undertake DNA screening. When asked about the optimal age of screening, most (56%) favoured early adulthood (aged 18–40 years) rather than at birth or childhood. Many respondents would prefer samples and data be kept for re-screening (36%) or research use (43%); some preferred samples to be destroyed (21%). Issues that decrease likelihood of participation included privacy (75%) and insurance (86%) implications.ConclusionOur study demonstrates public willingness to participate in population DNA screening in Australia, and identifies barriers to participation, to be addressed in the design of screening programmes. Results are informing the development of a pilot national DNA screening programme.
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McCormick CZ, Yu KD, Johns A, Campbell-Salome G, Hallquist MLG, Sturm AC, Buchanan AH. Investigating Psychological Impact after Receiving Genetic Risk Results-A Survey of Participants in a Population Genomic Screening Program. J Pers Med 2022; 12:1943. [PMID: 36556164 PMCID: PMC9781266 DOI: 10.3390/jpm12121943] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 11/17/2022] [Accepted: 11/19/2022] [Indexed: 11/24/2022] Open
Abstract
Genomic screening programs have potential to benefit individuals who may not be clinically ascertained, but little is known about the psychological impact of receiving genetic results in this setting. The current study sought to further the understanding of individuals’ psychological response to receiving an actionable genetic test result from genomic screening. Telephone surveys were conducted with patient-participants at 6 weeks and 6 months post genetic result disclosure between September 2019 and May 2021 and assessed emotional response to receiving results via the FACToR, PANAS, and decision regret scales. Overall, 354 (29.4%) study participants completed both surveys. Participants reported moderate positive emotions and low levels of negative emotions, uncertainty, privacy concern, and decision regret over time. There were significant decreases in negative emotions (p = 0.0004) and uncertainty (p = 0.0126) between time points on the FACToR scale. “Interested” was the highest scoring discrete emotion (T1 3.6, T2 3.3, scale 0−5) but was significantly lower at 6 months (<0.0001). Coupled with other benefits of genomic screening, these results of modest psychological impact waning over time adds support to clinical utility of population genomic screening programs. However, questions remain regarding how to elicit an emotional response that motivates behavior change without causing psychological harm.
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Affiliation(s)
| | | | - Alicia Johns
- Department of Population Health Sciences, Geisinger, Danville, PA 17822, USA
| | - Gemme Campbell-Salome
- Department of Genomic Health, Geisinger, Danville, PA 17822, USA
- Department of Population Health Sciences, Geisinger, Danville, PA 17822, USA
| | | | - Amy C. Sturm
- Department of Genomic Health, Geisinger, Danville, PA 17822, USA
- 23andMe, Sunnyvale, CA 94086, USA
| | - Adam H. Buchanan
- Department of Genomic Health, Geisinger, Danville, PA 17822, USA
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36
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Blout Zawatsky CL, Leonhard JR, Bell M, Moore MM, Petry NJ, Platt DM, Green RC, Hajek C, Christensen KD. Workforce Considerations When Building a Precision Medicine Program. J Pers Med 2022; 12:1929. [PMID: 36422106 PMCID: PMC9692406 DOI: 10.3390/jpm12111929] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 10/11/2022] [Accepted: 11/12/2022] [Indexed: 11/22/2022] Open
Abstract
This paper describes one healthcare system's approach to strategically deploying genetic specialists and pharmacists to support the implementation of a precision medicine program. In 2013, Sanford Health initiated the development of a healthcare system-wide precision medicine program. Here, we report the necessary staffing including the genetic counselors, genetic counseling assistants, pharmacists, and geneticists. We examined the administrative and electronic medical records data to summarize genetic referrals over time as well as the uptake and results of an enterprise-wide genetic screening test. Between 2013 and 2020, the number of genetic specialists employed at Sanford Health increased by 190%, from 10.1 full-time equivalents (FTEs) to 29.3 FTEs. Over the same period, referrals from multiple provider types to genetic services increased by 423%, from 1438 referrals to 7517 referrals. Between 2018 and 2020, 11,771 patients received a genetic screening, with 4% identified with potential monogenic medically actionable predisposition (MAP) findings and 95% identified with at least one informative pharmacogenetic result. Of the MAP-positive patients, 85% had completed a session with a genetics provider. A strategic workforce staffing and deployment allowed Sanford Health to manage a new genetic screening program, which prompted a large increase in genetic referrals. This approach can be used as a template for other healthcare systems interested in the development of a precision medicine program.
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Affiliation(s)
- Carrie L. Blout Zawatsky
- Genomes2People, Department of Medicine (Genetics), Brigham and Women’s Hospital, Boston, MA 02115, USA
- Broad Institute, Cambridge, MA 02142, USA
- Precision Population Health, Ariadne Labs, Boston, MA 02115, USA
- The MGH Institute of Health Professions, Boston, MA 02115, USA
| | | | - Megan Bell
- Department of Genetics, Sanford Health, Sioux Falls, SD 57117, USA
- Department of Genetic Counseling, Augustana University, Sioux Falls, SD 57117, USA
| | | | - Natasha J. Petry
- Department of Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57117, USA
- Department of Pharmacy Practice, North Dakota State University, Fargo, ND 58105, USA
| | - Dylan M. Platt
- Department of Genetics, Sanford Health, Sioux Falls, SD 57117, USA
- Department of Genetic Counseling, Augustana University, Sioux Falls, SD 57117, USA
| | - Robert C. Green
- Genomes2People, Department of Medicine (Genetics), Brigham and Women’s Hospital, Boston, MA 02115, USA
- Broad Institute, Cambridge, MA 02142, USA
- Precision Population Health, Ariadne Labs, Boston, MA 02115, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Catherine Hajek
- Department of Genetics, Sanford Health, Sioux Falls, SD 57117, USA
- Sanford School of Medicine, University of South Dakota, Sioux Falls, SD 57117, USA
- Helix, San Mateo, CA 94401, USA
| | - Kurt D. Christensen
- Broad Institute, Cambridge, MA 02142, USA
- Department of Population Medicine, Harvard Medical School, Boston, MA 02215, USA
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
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Blumling AA, Prows CA, Harr MH, Chung WK, Clayton EW, Holm IA, Wiesner GL, Connolly JJ, Harley JB, Hakonarson H, McGowan ML, Miller EM, Myers MF. Outcomes of Returning Medically Actionable Genomic Results in Pediatric Research. J Pers Med 2022; 12:1910. [PMID: 36422086 PMCID: PMC9694255 DOI: 10.3390/jpm12111910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 11/07/2022] [Accepted: 11/09/2022] [Indexed: 11/17/2022] Open
Abstract
PURPOSE The electronic Medical Records and Genomics (eMERGE) Phase III study was undertaken to assess clinical utility of returning medically actionable genomic screening results. We assessed pediatric clinical outcomes following return of pathogenic/likely pathogenic (P/LP) variants in autosomal dominant conditions with available effective interventions. METHODS The two eMERGE III pediatric sites collected outcome data and assessed changes in medical management at 6 and 12 months. RESULTS We returned P/LP results to 29 participants with outcome data. For 23 of the 29 participants, the P/LP results were previously unknown. Five of the 23 participants were already followed for conditions related to the P/LP variant. Of those receiving novel results and not being followed for the condition related to the P/LP result (n = 18), 14 (77.8%) had a change in healthcare after return of results (RoR). Following RoR, cascade testing of family members occurred for 10 of 23 (43.5%). CONCLUSIONS The most common outcomes post-RoR included imaging/laboratory testing and health behavior recommendations. A change in healthcare was documented in 77.8% of those receiving results by 6 months. Our findings demonstrate how return of genomic screening results impacts healthcare in pediatric populations.
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Affiliation(s)
- Amy A. Blumling
- Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Cynthia A. Prows
- Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Margaret H. Harr
- Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Wendy K. Chung
- Department of Pediatrics, Columbia University, New York, NY 10032, USA
| | - Ellen Wright Clayton
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Ingrid A. Holm
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA 02115, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | - Georgia L. Wiesner
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - John J. Connolly
- Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - John B. Harley
- US Department of Veterans Affairs Medical Center, Cincinnati, OH 45220, USA
| | - Hakon Hakonarson
- Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Michelle L. McGowan
- Biomedical Ethics Research Program, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
- Department of Women’s, Gender, and Sexuality Studies, College of Arts and Sciences, University of Cincinnati, Cincinnati, OH 45221, USA
| | - Erin M. Miller
- Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA
- Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, OH 45267, USA
| | - Melanie F. Myers
- Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA
- Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, OH 45267, USA
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38
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Chan SH, Bylstra Y, Teo JX, Kuan JL, Bertin N, Gonzalez-Porta M, Hebrard M, Tirado-Magallanes R, Tan JHJ, Jeyakani J, Li Z, Chai JF, Chong YS, Davila S, Goh LL, Lee ES, Wong E, Wong TY, Prabhakar S, Liu J, Cheng CY, Eisenhaber B, Karnani N, Leong KP, Sim X, Yeo KK, Chambers JC, Tai ES, Tan P, Jamuar SS, Ngeow J, Lim WK, Gluckman PD, Goh DLM, Jain K, Kam S, Kassam I, Lakshmanan LN, Lee CG, Lee J, Lee SC, Lee YS, Li H, Lim CW, Lim TH, Loh M, Maurer-Stroh S, Mina TH, Mok SQ, Ng HK, Pua CJ, Riboli E, Rim TH, Sabanayagam C, Sim WC, Subramaniam T, Tan ES, Tan EK, Tantoso E, Tay D, Teo YY, Tham YC, Toh LXG, Tsai PK, van Dam RM, Veeravalli L, Khin-lin GW, Wilm A, Yang C, Yap F, Yew YW, Prabhakar S, Liu J, Cheng CY, Eisenhaber B, Karnani N, Leong KP, Sim X, Yeo KK, Chambers JC, Tai ES, Tan P, Jamuar SS, Ngeow J, Lim WK. Analysis of clinically relevant variants from ancestrally diverse Asian genomes. Nat Commun 2022; 13:6694. [PMID: 36335097 PMCID: PMC9637116 DOI: 10.1038/s41467-022-34116-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 10/12/2022] [Indexed: 11/06/2022] Open
Abstract
Asian populations are under-represented in human genomics research. Here, we characterize clinically significant genetic variation in 9051 genomes representing East Asian, South Asian, and severely under-represented Austronesian-speaking Southeast Asian ancestries. We observe disparate genetic risk burden attributable to ancestry-specific recurrent variants and identify individuals with variants specific to ancestries discordant to their self-reported ethnicity, mostly due to cryptic admixture. About 27% of severe recessive disorder genes with appreciable carrier frequencies in Asians are missed by carrier screening panels, and we estimate 0.5% Asian couples at-risk of having an affected child. Prevalence of medically-actionable variant carriers is 3.4% and a further 1.6% harbour variants with potential for pathogenic classification upon additional clinical/experimental evidence. We profile 23 pharmacogenes with high-confidence gene-drug associations and find 22.4% of Asians at-risk of Centers for Disease Control and Prevention Tier 1 genetic conditions concurrently harbour pharmacogenetic variants with actionable phenotypes, highlighting the benefits of pre-emptive pharmacogenomics. Our findings illuminate the diversity in genetic disease epidemiology and opportunities for precision medicine for a large, diverse Asian population.
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Affiliation(s)
- Sock Hoai Chan
- grid.410724.40000 0004 0620 9745Cancer Genetics Service, Division of Medical Oncology, National Cancer Centre Singapore, Singapore, 169610 Singapore ,grid.428397.30000 0004 0385 0924Oncology Academic Clinical Program, Duke-NUS Medical School, Singapore, 169857 Singapore ,grid.59025.3b0000 0001 2224 0361Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232 Singapore
| | - Yasmin Bylstra
- grid.4280.e0000 0001 2180 6431SingHealth Duke-NUS Institute of Precision Medicine, Singapore, 169609 Singapore
| | - Jing Xian Teo
- grid.4280.e0000 0001 2180 6431SingHealth Duke-NUS Institute of Precision Medicine, Singapore, 169609 Singapore
| | - Jyn Ling Kuan
- grid.4280.e0000 0001 2180 6431SingHealth Duke-NUS Institute of Precision Medicine, Singapore, 169609 Singapore
| | - Nicolas Bertin
- grid.418377.e0000 0004 0620 715XGenome Research Informatics & Data Science Platform, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672 Singapore
| | - Mar Gonzalez-Porta
- grid.418377.e0000 0004 0620 715XGenome Research Informatics & Data Science Platform, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672 Singapore
| | - Maxime Hebrard
- grid.418377.e0000 0004 0620 715XGenome Research Informatics & Data Science Platform, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672 Singapore
| | - Roberto Tirado-Magallanes
- grid.418377.e0000 0004 0620 715XGenome Research Informatics & Data Science Platform, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672 Singapore
| | - Joanna Hui Juan Tan
- grid.418377.e0000 0004 0620 715XGenome Research Informatics & Data Science Platform, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672 Singapore
| | - Justin Jeyakani
- grid.418377.e0000 0004 0620 715XGenome Research Informatics & Data Science Platform, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672 Singapore
| | - Zhihui Li
- grid.418377.e0000 0004 0620 715XGenome Research Informatics & Data Science Platform, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672 Singapore
| | - Jin Fang Chai
- grid.4280.e0000 0001 2180 6431Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 117549 Singapore
| | - Yap Seng Chong
- grid.4280.e0000 0001 2180 6431Department of Obstetrics & Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228 Singapore ,grid.452264.30000 0004 0530 269XSingapore Institute for Clinical Sciences, Singapore, 117609 Singapore
| | - Sonia Davila
- grid.4280.e0000 0001 2180 6431SingHealth Duke-NUS Institute of Precision Medicine, Singapore, 169609 Singapore ,grid.428397.30000 0004 0385 0924Cardiovascular and Metabolic Disorders Program, Duke-NUS Medical School, Singapore, 169857 Singapore ,grid.4280.e0000 0001 2180 6431SingHealth Duke-NUS Genomic Medicine Centre, Singapore, 168582 Singapore
| | - Liuh Ling Goh
- grid.240988.f0000 0001 0298 8161Personalized Medicine Service, Tan Tock Seng Hospital, Singapore, 308433 Singapore
| | - Eng Sing Lee
- grid.59025.3b0000 0001 2224 0361Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232 Singapore ,grid.466910.c0000 0004 0451 6215National Healthcare Group Polyclinics, Singapore, 138543 Singapore
| | - Eleanor Wong
- grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672 Singapore
| | - Tien Yin Wong
- grid.419272.b0000 0000 9960 1711Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751 Singapore
| | | | - Shyam Prabhakar
- grid.418377.e0000 0004 0620 715XLaboratory of Systems Biology and Data Analytics, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672 Singapore
| | - Jianjun Liu
- grid.418377.e0000 0004 0620 715XHuman Genomics, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672 Singapore ,grid.4280.e0000 0001 2180 6431Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228 Singapore
| | - Ching-Yu Cheng
- grid.419272.b0000 0000 9960 1711Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, 168751 Singapore ,grid.428397.30000 0004 0385 0924Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, 169857 Singapore
| | - Birgit Eisenhaber
- grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672 Singapore ,grid.418325.90000 0000 9351 8132Bioinformatics Institute, Agency for Science, Technology and Research, Singapore, 138671 Singapore
| | - Neerja Karnani
- grid.452264.30000 0004 0530 269XHuman Development, Singapore Institute for Clinical Sciences, Singapore, 117609 Singapore ,grid.418325.90000 0000 9351 8132Clinical Data Engagement, Bioinformatics Institute, Agency for Science, Technology and Research, Singapore, 138671 Singapore ,grid.4280.e0000 0001 2180 6431Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117596 Singapore
| | - Khai Pang Leong
- grid.240988.f0000 0001 0298 8161Personalized Medicine Service, Tan Tock Seng Hospital, Singapore, 308433 Singapore ,grid.240988.f0000 0001 0298 8161Department of Rheumatology, Allergy and Immunology, Tan Tock Seng Hospital, Singapore, 308433 Singapore
| | - Xueling Sim
- grid.4280.e0000 0001 2180 6431Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 117549 Singapore
| | - Khung Keong Yeo
- grid.4280.e0000 0001 2180 6431SingHealth Duke-NUS Institute of Precision Medicine, Singapore, 169609 Singapore ,grid.419385.20000 0004 0620 9905Department of Cardiology, National Heart Centre Singapore, Singapore, 169609 Singapore ,grid.428397.30000 0004 0385 0924Duke-NUS Medical School, Singapore, 169857 Singapore
| | - John C. Chambers
- grid.59025.3b0000 0001 2224 0361Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232 Singapore ,Precision Health Research Singapore (PRECISE), Singapore, 139234 Singapore ,grid.7445.20000 0001 2113 8111Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG UK
| | - E-Shyong Tai
- grid.4280.e0000 0001 2180 6431Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 117549 Singapore ,grid.4280.e0000 0001 2180 6431Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228 Singapore ,grid.428397.30000 0004 0385 0924Duke-NUS Medical School, Singapore, 169857 Singapore ,Precision Health Research Singapore (PRECISE), Singapore, 139234 Singapore
| | - Patrick Tan
- grid.4280.e0000 0001 2180 6431SingHealth Duke-NUS Institute of Precision Medicine, Singapore, 169609 Singapore ,grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672 Singapore ,Precision Health Research Singapore (PRECISE), Singapore, 139234 Singapore ,grid.428397.30000 0004 0385 0924Cancer & Stem Cell Biology Program, Duke-NUS Medical School, Singapore, 169857 Singapore ,grid.4280.e0000 0001 2180 6431Cancer Science Institute of Singapore, National University of Singapore, Singapore, 117599 Singapore
| | - Saumya S. Jamuar
- grid.4280.e0000 0001 2180 6431SingHealth Duke-NUS Institute of Precision Medicine, Singapore, 169609 Singapore ,grid.4280.e0000 0001 2180 6431SingHealth Duke-NUS Genomic Medicine Centre, Singapore, 168582 Singapore ,grid.414963.d0000 0000 8958 3388Genetics Service, Department of Paediatrics, KK Women’s and Children’s Hospital, Singapore, 229899 Singapore ,grid.428397.30000 0004 0385 0924Paediatric Academic Clinical Program, Duke-NUS Medical School, Singapore, 169857 Singapore
| | - Joanne Ngeow
- grid.410724.40000 0004 0620 9745Cancer Genetics Service, Division of Medical Oncology, National Cancer Centre Singapore, Singapore, 169610 Singapore ,grid.428397.30000 0004 0385 0924Oncology Academic Clinical Program, Duke-NUS Medical School, Singapore, 169857 Singapore ,grid.59025.3b0000 0001 2224 0361Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232 Singapore ,grid.185448.40000 0004 0637 0221Institute of Molecular and Cellular Biology, Agency for Science, Technology and Research, Singapore, 138673 Singapore
| | - Weng Khong Lim
- grid.4280.e0000 0001 2180 6431SingHealth Duke-NUS Institute of Precision Medicine, Singapore, 169609 Singapore ,grid.4280.e0000 0001 2180 6431SingHealth Duke-NUS Genomic Medicine Centre, Singapore, 168582 Singapore ,grid.428397.30000 0004 0385 0924Cancer & Stem Cell Biology Program, Duke-NUS Medical School, Singapore, 169857 Singapore
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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: 5] [Impact Index Per Article: 2.5] [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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Baker A, Tolwinski K, Atondo J, Davis FD, Goehringer J, Jones LK, Pisieczko CJ, Sturm AC, Williams JL, Williams MS, Rahm AK, Buchanan AH. Understanding the Patient Experience of Receiving Clinically Actionable Genetic Results from the MyCode Community Health Initiative, a Population-Based Genomic Screening Initiative. J Pers Med 2022; 12:jpm12091511. [PMID: 36143296 PMCID: PMC9501087 DOI: 10.3390/jpm12091511] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 09/06/2022] [Accepted: 09/07/2022] [Indexed: 11/16/2022] Open
Abstract
Understanding unselected individuals’ experiences receiving genetic results through population genomic screening is critical to advancing clinical utility and improving population health. We conducted qualitative interviews with individuals who received clinically actionable genetic results via the MyCode© Genomic Screening and Counseling program. We purposively sampled cohorts to seek diversity in result-related disease risk (e.g., cancer or cardiovascular) and in personal or family history of related diseases. Transcripts were analyzed using a two-step inductive coding process of broad thematic analysis followed by in-depth coding of each theme. Four thematic domains identified across all cohorts were examined: process assessment, psychosocial response, behavioral change due to the genetic result, and family communication. Coding of 63 interviews among 60 participants revealed that participants were satisfied with the results disclosure process, initially experienced a range of positive, neutral, and negative psychological reactions to results, adjusted positively to results over time, undertook clinically indicated actions in response to results, and communicated results with relatives to whom they felt emotionally close. Our findings of generally favorable responses to receiving clinically actionable genetic results via a genomic screening program may assuage fear of patient distress in such programs and guide additional biobanks, genomic screening programs, and research studies.
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Affiliation(s)
- Anna Baker
- Department of Psychology, Bucknell University, Lewisburg, PA 17837, USA or
- Department of Psychology, Clemson University, Clemson, SC 29634, USA
| | - Kasia Tolwinski
- Biomedical Ethics Unit, McGill University, Montreal, QC H3A 0G4, Canada
| | - Jamie Atondo
- Department of Genomic Health, Geisinger, Danville, PA 17822, USA or
| | | | | | - Laney K. Jones
- Department of Genomic Health, Geisinger, Danville, PA 17822, USA or
- Heart and Vascular Institute, Geisinger, Danville, PA 17822, USA
| | | | - Amy C. Sturm
- Department of Genomic Health, Geisinger, Danville, PA 17822, USA or
- 23andMe, Sunnyvale, CA 94086, USA
| | | | - Marc S. Williams
- Department of Genomic Health, Geisinger, Danville, PA 17822, USA or
| | | | - Adam H. Buchanan
- Department of Genomic Health, Geisinger, Danville, PA 17822, USA or
- Correspondence:
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Savatt JM, Shimelis H, Moreno-De-Luca A, Strande NT, Oetjens MT, Ledbetter DH, Martin CL, Myers SM, Finucane BM. Frequency of truncating FLCN variants and Birt-Hogg-Dubé-associated phenotypes in a health care system population. Genet Med 2022; 24:1857-1866. [PMID: 35639097 PMCID: PMC9703446 DOI: 10.1016/j.gim.2022.05.006] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 05/05/2022] [Accepted: 05/06/2022] [Indexed: 02/05/2023] Open
Abstract
PURPOSE Penetrance estimates of Birt-Hogg-Dubé syndrome (BHD)-associated cutaneous, pulmonary, and kidney manifestations are based on clinically ascertained families. In a health care system population, we used a genetics-first approach to estimate the prevalence of pathogenic/likely pathogenic (P/LP) truncating variants in FLCN, which cause BHD, and the penetrance of BHD-related phenotypes. METHODS Exomes from 135,990 patient-participants in Geisinger's MyCode cohort were assessed for P/LP truncating FLCN variants. BHD-related phenotypes were evaluated from electronic health records. Association between P/LP FLCN variants and BHD-related phenotypes was assessed using Firth's logistic regression. RESULTS P/LP truncating FLCN variants were identified in 35 individuals (1 in 3234 unrelated individuals), 68.6% of whom had BHD-related phenotype(s), including cystic lung disease (65.7%), pneumothoraces (17.1%), cutaneous manifestations (8.6%), and kidney cancer (2.9%). A total of 4 (11.4%) individuals had prior clinical BHD diagnoses. CONCLUSION In this health care population, the frequency of P/LP truncating FLCN variants is 60 times higher than the previously reported prevalence. Although most variant-positive individuals had BHD-related phenotypes, a minority were previously clinically diagnosed, likely because cutaneous manifestations, pneumothoraces, and kidney cancer were observed at lower frequencies than in clinical cohorts. Improved clinical recognition of cystic lung disease and education concerning its association with FLCN variants could prompt evaluation for BHD.
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Affiliation(s)
- Juliann M. Savatt
- Autism & Developmental Medicine Institute, Geisinger, Lewisburg, Pennsylvania,Genomic Medicine Institute, Geisinger, Danville, Pennsylvania
| | - Hermela Shimelis
- Autism & Developmental Medicine Institute, Geisinger, Lewisburg, Pennsylvania
| | - Andres Moreno-De-Luca
- Autism & Developmental Medicine Institute, Geisinger, Lewisburg, Pennsylvania,Genomic Medicine Institute, Geisinger, Danville, Pennsylvania,Department of Radiology, Geisinger, Danville, Pennsylvania
| | - Natasha T. Strande
- Autism & Developmental Medicine Institute, Geisinger, Lewisburg, Pennsylvania,Genomic Medicine Institute, Geisinger, Danville, Pennsylvania
| | - Matthew T. Oetjens
- Autism & Developmental Medicine Institute, Geisinger, Lewisburg, Pennsylvania
| | - David H. Ledbetter
- Autism & Developmental Medicine Institute, Geisinger, Lewisburg, Pennsylvania,Genomic Medicine Institute, Geisinger, Danville, Pennsylvania
| | - Christa Lese Martin
- Autism & Developmental Medicine Institute, Geisinger, Lewisburg, Pennsylvania,Genomic Medicine Institute, Geisinger, Danville, Pennsylvania
| | - Scott M. Myers
- Autism & Developmental Medicine Institute, Geisinger, Lewisburg, Pennsylvania
| | - Brenda M. Finucane
- Autism & Developmental Medicine Institute, Geisinger, Lewisburg, Pennsylvania
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Nurses’ Knowledge, Attitudes, Confidence, and Practices with Genetics and Genomics: A Theory-Informed Integrative Review Protocol. J Pers Med 2022; 12:jpm12091358. [PMID: 36143143 PMCID: PMC9505976 DOI: 10.3390/jpm12091358] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 08/19/2022] [Accepted: 08/21/2022] [Indexed: 11/16/2022] Open
Abstract
Introduction: As key healthcare providers, nurses require genomic competency to fulfil their professional obligations in the genomic era. Prior research suggests that nurses have limited competency with genomics-informed practice. Concepts in the Rogers’ Diffusion of Innovation (DOI) theory (i.e., knowledge, attitudes, and attributes of innovation adopters) provide a framework to understand the process of adoption of innovations, such as genomics, across organizations. We aim to synthesize what is known about the adoption of genomics across nursing within the DOI framework to identify gaps and opportunities to enact sustained adoption of genomics in nursing. Methods and analysis: An integrative literature review, following Whittemore and Knafl’s five steps, will be conducted to evaluate qualitative, quantitative, and mixed-method primary studies that meet inclusion and exclusion criteria. The MEDLINE, PsychINFO, CINAHL, Cochrane, and Sociological Abstracts electronic databases will be searched in addition to the ancestry search method. Two researchers will perform independent screening of studies, quality appraisal using the Mixed-Methods Appraisal Tool, and data analysis using the narrative synthesis method. Disagreements will be resolved by a third reviewer. Findings in this review could be used to develop theory- and evidence-informed strategies to support the sustained adoption of genomics in nursing.
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Hutchcraft ML, Zhang S, Lin N, Gottschalk GL, Keck JW, Belcher EA, Sears C, Wang C, Liu K, Dietz LE, Pickarski JC, Wei S, Cardarelli R, DiPaola RS, Kolesar JM. Real-World Evaluation of a Population Germline Genetic Screening Initiative for Family Medicine Patients. J Pers Med 2022; 12:1297. [PMID: 36013246 PMCID: PMC9410316 DOI: 10.3390/jpm12081297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Revised: 08/04/2022] [Accepted: 08/05/2022] [Indexed: 11/30/2022] Open
Abstract
Hereditary factors contribute to disease development and drug pharmacokinetics. The risk of hereditary disease development can be attenuated or eliminated by early screening or risk reducing interventions. The purpose of this study was to assess the clinical utility of germline medical exome sequencing in patients recruited from a family medicine clinic and compare the mutation frequency of hereditary predisposition genes to established general population frequencies. At the University of Kentucky, 205 family medicine patients underwent sequencing in a Clinical Laboratory Improvement Amendments of 1988-compliant laboratory to identify clinically actionable genomic findings. The study identified pathogenic or likely pathogenic genetic variants-classified according to the American College of Medical Genetics and Genomics variant classification guidelines-and actionable pharmacogenomic variants, as defined by the Clinical Pharmacogenetics Implementation Consortium. Test results for patients with pharmacogenomic variants and pathogenic or likely pathogenic variants were returned to the participant and enrolling physician. Hereditary disease predisposition gene mutations in APOB, BRCA2, MUTYH, CACNA1S, DSC2, KCNQ1, LDLR, SCN5A, or SDHB were identified in 6.3% (13/205) of the patients. Nine of 13 (69.2%) underwent subsequent clinical interventions. Pharmacogenomic variants were identified in 76.1% (156/205) of patients and included 4.9% (10/205) who were prescribed a medication that had pharmacogenomic implications. Family physicians changed medications for 1.5% (3/205) of patients to prevent toxicity. In this pilot study, we found that with systemic support, germline genetic screening initiatives were feasible and clinically beneficial in a primary care setting.
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Affiliation(s)
- Megan Leigh Hutchcraft
- Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, University of Kentucky Markey Cancer Center, Lexington, KY 40536, USA
| | - Shulin Zhang
- Department of Pathology and Laboratory Medicine, University of Kentucky Chandler Medical Center, Lexington, KY 40536, USA
| | - Nan Lin
- Department of Pharmacy Practice and Science, University of Kentucky College of Pharmacy, Lexington, KY 40506, USA
| | - Ginny Lee Gottschalk
- Department of Family and Community Medicine, University of Kentucky Chandler Medical Center, Lexington, KY 40536, USA
| | - James W. Keck
- Department of Family and Community Medicine, University of Kentucky Chandler Medical Center, Lexington, KY 40536, USA
| | - Elizabeth A. Belcher
- Department of Clinical Research, University of Kentucky Markey Cancer Center, Lexington, KY 40536, USA
| | - Catherine Sears
- Department of Pathology and Laboratory Medicine, University of Kentucky Chandler Medical Center, Lexington, KY 40536, USA
| | - Chi Wang
- Shared Resource Facility, University of Kentucky Markey Cancer Center, Lexington, KY 40536, USA
- Division of Cancer Biostatistics, Department of Internal Medicine, University of Kentucky College of Medicine, Lexington, KY 40506, USA
| | - Kun Liu
- Dr. Bing Zhang Department of Statistics, University of Kentucky, Lexington, KY 40536, USA
| | - Lauren E. Dietz
- Department of Pharmacy Practice and Science, University of Kentucky College of Pharmacy, Lexington, KY 40506, USA
| | | | - Sainan Wei
- Department of Pathology and Laboratory Medicine, University of Kentucky Chandler Medical Center, Lexington, KY 40536, USA
| | - Roberto Cardarelli
- Department of Family and Community Medicine, University of Kentucky Chandler Medical Center, Lexington, KY 40536, USA
| | - Robert S. DiPaola
- University of Kentucky Markey Cancer Center, Lexington, KY 40536, USA
| | - Jill M. Kolesar
- Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, University of Kentucky Markey Cancer Center, Lexington, KY 40536, USA
- Department of Pharmacy Practice and Science, University of Kentucky College of Pharmacy, Lexington, KY 40506, USA
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Rossini L, Durante C, Bresolin S, Opocher E, Marzollo A, Biffi A. Diagnostic Strategies and Algorithms for Investigating Cancer Predisposition Syndromes in Children Presenting with Malignancy. Cancers (Basel) 2022; 14:cancers14153741. [PMID: 35954404 PMCID: PMC9367486 DOI: 10.3390/cancers14153741] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 07/22/2022] [Accepted: 07/25/2022] [Indexed: 02/04/2023] Open
Abstract
Simple Summary Here we provide an overview of several genetically determined conditions that predispose to the development of solid and hematologic malignancies in children. Diagnosing these conditions, whose prevalence is estimated around 10% in children with cancer, is useful to warrant personalized oncologic treatment and follow-up, as well as psychological and genetic counseling to these children and their families. We reviewed the most recent studies focusing on the prevalence of cancer predisposition syndromes in cancer-bearing children and the most-used clinical screening tools. Our work highlighted the value of clinical screening tools in the management of young cancer patients, especially in settings where genetic testing is not promptly accessible. Abstract In the past recent years, the expanding use of next-generation sequencing has led to the discovery of new cancer predisposition syndromes (CPSs), which are now known to be responsible for up to 10% of childhood cancers. As knowledge in the field is in constant evolution, except for a few “classic” CPSs, there is no consensus about when and how to perform germline genetic diagnostic studies in cancer-bearing children. Several clinical screening tools have been proposed to help identify the patients who carry higher risk, with heterogeneous strategies and results. After introducing the main clinical and molecular features of several CPSs predisposing to solid and hematological malignancies, we compare the available clinical evidence on CPS prevalence in pediatric cancer patients and on the most used decision-support tools in identifying the patients who could benefit from genetic counseling and/or direct genetic testing. This analysis highlighted that a personalized stepwise approach employing clinical screening tools followed by sequencing in high-risk patients might be a reasonable and cost-effective strategy in the care of children with cancer.
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Affiliation(s)
- Linda Rossini
- Pediatric Hematology, Oncology and Stem Cell Transplant Division, Padua University Hospital, Via Giustiniani 3, 35128 Padua, Italy; (L.R.); (C.D.); (S.B.); (E.O.)
| | - Caterina Durante
- Pediatric Hematology, Oncology and Stem Cell Transplant Division, Padua University Hospital, Via Giustiniani 3, 35128 Padua, Italy; (L.R.); (C.D.); (S.B.); (E.O.)
| | - Silvia Bresolin
- Pediatric Hematology, Oncology and Stem Cell Transplant Division, Padua University Hospital, Via Giustiniani 3, 35128 Padua, Italy; (L.R.); (C.D.); (S.B.); (E.O.)
- Maternal and Child Health Department, Padua University, Via Giustiniani, 3, 35128 Padua, Italy
| | - Enrico Opocher
- Pediatric Hematology, Oncology and Stem Cell Transplant Division, Padua University Hospital, Via Giustiniani 3, 35128 Padua, Italy; (L.R.); (C.D.); (S.B.); (E.O.)
| | - Antonio Marzollo
- Pediatric Hematology, Oncology and Stem Cell Transplant Division, Padua University Hospital, Via Giustiniani 3, 35128 Padua, Italy; (L.R.); (C.D.); (S.B.); (E.O.)
- Correspondence: (A.M.); (A.B.)
| | - Alessandra Biffi
- Pediatric Hematology, Oncology and Stem Cell Transplant Division, Padua University Hospital, Via Giustiniani 3, 35128 Padua, Italy; (L.R.); (C.D.); (S.B.); (E.O.)
- Maternal and Child Health Department, Padua University, Via Giustiniani, 3, 35128 Padua, Italy
- Correspondence: (A.M.); (A.B.)
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Lessons Learned from the Pilot Phase of a Population-Wide Genomic Screening Program: Building the Base to Reach a Diverse Cohort of 100,000 Participants. J Pers Med 2022; 12:jpm12081228. [PMID: 36013178 PMCID: PMC9410232 DOI: 10.3390/jpm12081228] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 07/18/2022] [Indexed: 11/17/2022] Open
Abstract
Background and Objectives: Genomic information is increasingly relevant for disease prevention and risk management at the individual and population levels. Screening healthy adults for Tier 1 conditions of hereditary breast and ovarian cancer, Lynch syndrome, and familial hypercholesterolemia using a population-based approach can help identify the 1−2% of the US population at increased risk of developing diseases associated with these conditions and tailor prevention strategies. Our objective is to report findings from an implementation science study that evaluates multi-level facilitators and barriers to implementation of the In Our DNA SC population-wide genomic screening initiative. Methods: We established an IMPACTeam (IMPlementAtion sCience for In Our DNA SC Team) to evaluate the pilot phase using principles of implementation science. We used a parallel convergent mixed methods approach to assess the Reach, Implementation, and Effectiveness outcomes from the RE-AIM implementation science framework during the pilot phase of In Our DNA SC. Quantitative assessment included the examination of frequencies and response rates across demographic categories using chi-square tests. Qualitative data were audio-recorded and transcribed, with codes developed by the study team based on the semi-structured interview guide. Results: The pilot phase (8 November 2021, to 7 March 2022) included recruitment from ten clinics throughout South Carolina. Reach indicators included enrollment rate and representativeness. A total of 23,269 potential participants were contacted via Epic’s MyChart patient portal with 1976 (8.49%) enrolled. Black individuals were the least likely to view the program invitation (28.9%) and take study-related action. As a result, there were significantly higher enrollment rates among White (10.5%) participants than Asian (8.71%) and Black (3.46%) individuals (p < 0.0001). Common concerns limiting reach and participation included privacy and security of results and the impact participation would have on health or life insurance. Facilitators included family or personal history of a Tier 1 condition, prior involvement in genetic testing, self-interest, and altruism. Assessment of implementation (i.e., adherence to protocols/fidelity to protocols) included sample collection rate (n = 1104, 55.9%) and proportion of samples needing recollection (n = 19, 1.7%). There were no significant differences in sample collection based on demographic characteristics. Implementation facilitators included efficient collection processes and enthusiastic clinical staff. Finally, we assessed the effectiveness of the program, finding low dropout rates (n = 7, 0.35%), the identification of eight individuals with Tier 1 conditions (0.72% positive), and high rates of follow-up genetic counseling (87.5% completion). Conclusion: Overall, Asian and Black individuals were less engaged, with few taking any study-related actions. Strategies to identify barriers and promoters for the engagement of diverse populations are needed to support participation. Once enrolled, individuals had high rates of completing the study and follow-up engagement with genetic counselors. Findings from the pilot phase of In Our DNA SC offer opportunities for improvement as we expand the program and can provide guidance to organizations seeking to begin efforts to integrate population-wide genomic screening.
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46
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Educational Programme for Cancer Nurses in Genetics, Health Behaviors and Cancer Prevention: A Multidisciplinary Consensus Study. J Pers Med 2022; 12:jpm12071104. [PMID: 35887601 PMCID: PMC9318790 DOI: 10.3390/jpm12071104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 06/26/2022] [Accepted: 07/01/2022] [Indexed: 11/21/2022] Open
Abstract
(1) Background: Most common hereditary cancers in Europe have been associated with lifestyle behaviors, and people affected are lacking follow up care. However, access to education programmes to increase knowledge on cancer and genetics and promote healthy lifestyle behaviors in people at high risk of cancer is scarce. This affects the quality of care of people with a hereditary risk of cancer. This study aimed to reach a multidisciplinary consensus on topics and competencies and competencies that cancer nurses need in relation to cancer, genetics, and health promotion. (2) Methods: A two-round online Delphi study was undertaken. Experts in cancer and genetics were asked to assess the relevance of eighteen items and to suggest additional terms. Consensus was defined as an overall agreement of at least 75%. (3) Results: A total of 74 multiprofessional experts from all around the world participated in this study including healthcare professionals working in genetics (39%), researchers in cancer and genetics (31%) and healthcare professionals with cancer patients (30%). Thirteen additional items were proposed. A total of thirty-one items reached consensus. (4) Conclusions: This multidisciplinary consensus study provide the essential elements to build an educational programme to increase cancer nurses’ skills to support the complex care of people living with a higher risk of cancer including addressing lifestyle behaviors. All professionals highlighted the importance of cancer nurses increasing their skills in cancer and genetics.
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Lu T, Forgetta V, Richards JB, Greenwood CMT. Polygenic risk score as a possible tool for identifying familial monogenic causes of complex diseases. Genet Med 2022; 24:1545-1555. [PMID: 35460399 DOI: 10.1016/j.gim.2022.03.022] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 03/29/2022] [Accepted: 03/30/2022] [Indexed: 01/13/2023] Open
Abstract
PURPOSE The study aimed to evaluate whether polygenic risk scores could be helpful in addition to family history for triaging individuals to undergo deep-depth diagnostic sequencing for identifying monogenic causes of complex diseases. METHODS Among 44,550 exome-sequenced European ancestry UK Biobank participants, we identified individuals with a clinically reported or computationally predicted monogenic pathogenic variant for breast cancer, bowel cancer, heart disease, diabetes, or Alzheimer disease. We derived polygenic risk scores for these diseases. We tested whether a polygenic risk score could identify rare pathogenic variant heterozygotes among individuals with a parental disease history. RESULTS Monogenic causes of complex diseases were more prevalent among individuals with a parental disease history than in the rest of the population. Polygenic risk scores showed moderate discriminative power to identify familial monogenic causes. For instance, we showed that prescreening the patients with a polygenic risk score for type 2 diabetes can prioritize individuals to undergo diagnostic sequencing for monogenic diabetes variants and reduce needs for such sequencing by up to 37%. CONCLUSION Among individuals with a family history of complex diseases, those with a low polygenic risk score are more likely to have monogenic causes of the disease and could be prioritized to undergo genetic testing.
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Affiliation(s)
- Tianyuan Lu
- Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada; Quantitative Life Sciences Program, McGill University, Montreal, Quebec, Canada
| | - Vincenzo Forgetta
- Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
| | - John Brent Richards
- Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada; Department of Human Genetics, Faculty of Medicine and Health Sciences, McGill University, Montreal, Quebec, Canada; Department of Twin Research and Genetic Epidemiology, School of Life Course & Population Sciences, Faculty of Life Sciences & Medicine, King's College London, London, United Kingdom
| | - Celia M T Greenwood
- Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada; Department of Human Genetics, Faculty of Medicine and Health Sciences, McGill University, Montreal, Quebec, Canada; Department of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine and Health Sciences, McGill University, Montreal, Quebec, Canada; Gerald Bronfman Department of Oncology, Gerald Bronfman Department of Oncology, McGill University, McGill University, Montreal, Quebec, Canada.
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Savatt JM, Ortiz NM, Thone GM, McDonald WS, Kelly MA, Berry ASF, Alvi MM, Hallquist MLG, Malinowski J, Purdy NC, Williams MS, Sturm AC, Buchanan AH. Observational study of population genomic screening for variants associated with endocrine tumor syndromes in a large, healthcare-based cohort. BMC Med 2022; 20:205. [PMID: 35668420 PMCID: PMC9172012 DOI: 10.1186/s12916-022-02375-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 04/12/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND In current care, patients' personal and self-reported family histories are primarily used to determine whether genetic testing for hereditary endocrine tumor syndromes (ETS) is indicated. Population genomic screening for other conditions has increased ascertainment of individuals with pathogenic/likely pathogenic (P/LP) variants, leading to improved management and earlier diagnoses. It is unknown whether such benefits occur when screening broader populations for P/LP ETS variants. This manuscript assesses clinical utility outcomes of a large, unselected, healthcare-based genomic screening program by describing personal and family history of syndrome-related features, risk management behaviors after result disclosure, and rates of relevant post-disclosure diagnoses in patient-participants with P/LP ETS variants. METHODS Observational study of individuals informed of a P/LP variant in MEN1, RET, SDHAF2, SDHB, SDHC, SDHD, or VHL through Geisinger's MyCode Community Health Initiative between June 2016 and October 2019. Electronic health records (EHRs) of participants were evaluated for a report of pre-disclosure personal and self-reported family histories and post-disclosure risk management and diagnoses. RESULTS P/LP variants in genes of interest were identified in 199 of 130,490 (1 in 656) adult Geisinger MyCode patient-participants, 80 of which were disclosed during the study period. Eighty-one percent (n = 65) did not have prior evidence of the result in their EHR and, because they were identified via MyCode, were included in further analyses. Five participants identified via MyCode (8%) had a personal history of syndrome-related features; 16 (25%) had a positive self-reported family history. Time from result disclosure to EHR review was a median of 0.7 years. Post-disclosure, 36 (55.4%) completed a recommended risk management behavior; 11 (17%) were diagnosed with a syndrome-related neoplasm after completing a risk management intervention. CONCLUSIONS Broader screening for pathogenic/likely pathogenic variants associated with endocrine tumor syndromes enables detection of at-risk individuals, leads to the uptake of risk management, and facilitates relevant diagnoses. Further research will be necessary to continue to determine the clinical utility of screening diverse, unselected populations for such variants.
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Affiliation(s)
| | - Nicole M Ortiz
- Genomic Medicine Institute, Geisinger, Danville, PA, USA
| | | | | | | | | | - Madiha M Alvi
- Endocrinology, Diabetes, and Metabolism, Geisinger, Danville, PA, USA.,Geisinger Commonwealth School of Medicine, Scranton, PA, USA
| | | | | | - Nicholas C Purdy
- Geisinger Commonwealth School of Medicine, Scranton, PA, USA.,Otolaryngology, Geisinger, Danville, PA, USA
| | - Marc S Williams
- Genomic Medicine Institute, Geisinger, Danville, PA, USA.,Geisinger Commonwealth School of Medicine, Scranton, PA, USA
| | - Amy C Sturm
- Genomic Medicine Institute, Geisinger, Danville, PA, USA.,Geisinger Commonwealth School of Medicine, Scranton, PA, USA.,Heart and Vascular Institute, Geisinger, Danville, PA, USA
| | - Adam H Buchanan
- Genomic Medicine Institute, Geisinger, Danville, PA, USA.,Geisinger Commonwealth School of Medicine, Scranton, PA, USA
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Makhnoon S, Maki KG, Yu R, Peterson SK, Shete S. Are beliefs about the importance of genetics for cancer prevention and early detection associated with high risk cancer genetic testing in the U.S. Population? Prev Med Rep 2022; 27:101781. [PMID: 35378849 PMCID: PMC8976149 DOI: 10.1016/j.pmedr.2022.101781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 03/18/2022] [Accepted: 03/26/2022] [Indexed: 11/10/2022] Open
Abstract
Public attitudes towards germline genetic testing for inherited cancers have been found to be generally positive. Past research demonstrated that diverse causal beliefs and contextual factors are associated with uptake of genetic testing. However, it is unclear how beliefs about genetically informed cancer prevention and early detection ultimately shape testing behaviors. We used data from the National Health Information National Trends Survey (HINTS 5 Cycle 4) to evaluate these beliefs and the relationship between beliefs related to cancer genetics and participation in cancer genetic testing. Overall, 5.24% of the total weighted sample underwent cancer genetic testing, of whom 70.5% (n = 141) had no personal history of cancer, whereas others had a personal diagnosis of breast, ovarian, or colorectal cancer (23.0%), or other cancers (6.5%). In adjusted multivariable analysis, testing was positively associated with personal history of breast, ovarian, or colorectal cancer (OR = 28.37, 95% CI: 10.19–79.04), female sex (OR = 2.97, 95% CI: 1.41–6.26), having high cancer worry (OR = 4.78, 95%: 2.19–10.45), and negatively associated with being Hispanic (OR = 0.37, 95%: 0.16–0.86) or non-Hispanic Asian (OR = 0.12, 95% CI: 0.04–0.33). Belief in the importance of genetics for early detection of cancer was associated with testing (OR = 18.03, 95% CI: 4.07–79.79), whereas belief in the importance of genetics for cancer prevention was not. The association between testing and belief about the importance of genetics for early detection of cancer, but not cancer prevention, is a surprising finding that warrants further research. Better understanding of these beliefs and their potential impact on test uptake may inform population genetic testing efforts.
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Jones LK, Strande NT, Calvo EM, Chen J, Rodriguez G, McCormick CZ, Hallquist MLG, Savatt JM, Rocha H, Williams MS, Sturm AC, Buchanan AH, Glasgow RE, Martin CL, Rahm AK. A RE-AIM Framework Analysis of DNA-Based Population Screening: Using Implementation Science to Translate Research Into Practice in a Healthcare System. Front Genet 2022; 13:883073. [PMID: 35692820 PMCID: PMC9174580 DOI: 10.3389/fgene.2022.883073] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 05/04/2022] [Indexed: 11/13/2022] Open
Abstract
Introduction: DNA-based population screening has been proposed as a public health solution to identify individuals at risk for serious health conditions who otherwise may not present for medical care. The clinical utility and public health impact of DNA-based population screening is a subject of active investigation. Geisinger, an integrated healthcare delivery system, was one of the first healthcare systems to implement DNA screening programs (MyCode Community Health Initiative (MyCode) and clinical DNA screening pilot) that leverage exome data to identify individuals at risk for developing conditions with potential clinical actionability. Here, we demonstrate the use of an implementation science framework, RE-AIM (Reach, Effectiveness, Adoption, Implementation and Maintenance), to conduct a post-hoc evaluation and report outcomes from these two programs to inform the potential impact of DNA-based population screening. Methods: Reach and Effectiveness outcomes were determined from the MyCode research program, while Adoption and Implementation outcomes were measured using the clinical DNA screening pilot. Reach was defined as the number of patients who were offered and consented to participate in MyCode. Effectiveness of DNA screening was measured by reviewing MyCode program publications and synthesizing findings from themes. Adoption was measured by the total number of DNA screening tests ordered by clinicians at the clinical pilot sites. Implementation was assessed by interviewing a subset of clinical pilot clinicians about the deployment of and recommended adaptations to the pilot that could inform future program dissemination. Results: Reach: As of August 2020, 68% (215,078/316,612) of individuals approached to participate in the MyCode program consented. Effectiveness: Published evidence reported from MyCode demonstrates that DNA screening identifies at-risk individuals more comprehensively than clinical ascertainment based on phenotypes or personal/family history. Adoption: From July 2018 to June 2021, a total of 1,026 clinical DNA screening tests were ordered by 60 clinicians across the three pilot clinic sites. Implementation: Interviews with 14 clinicians practicing at the pilot clinic sites revealed motivation to provide patients with DNA screening results and yielded future implementation strategies. Conclusion: The RE-AIM framework offers a pragmatic solution to organize, analyze, and report outcomes across differently resourced and designed precision health programs that include genomic sequencing and return of clinically actionable genomic information.
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Affiliation(s)
- Laney K. Jones
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
- Heart and Vascular Institute, Geisinger, Danville, PA, United States
| | - Natasha T. Strande
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
- Autism & Developmental Medicine Institute, Geisinger, Danville, PA, United States
| | - Evan M. Calvo
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
| | - Jingheng Chen
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, United States
| | | | | | | | - Juliann M. Savatt
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
- Autism & Developmental Medicine Institute, Geisinger, Danville, PA, United States
| | - Heather Rocha
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
| | - Marc S. Williams
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
| | - Amy C. Sturm
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
- Heart and Vascular Institute, Geisinger, Danville, PA, United States
| | - Adam H. Buchanan
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
| | - Russell E. Glasgow
- University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Christa L. Martin
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
- Autism & Developmental Medicine Institute, Geisinger, Danville, PA, United States
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