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338 The Alabama Genomic Health Initiative: Integrating Genomic Medicine into Primary Care
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- Nita A Limdi, Devin Absher, Irf Asif, Lori Bateman, Greg Barsh, Kevin M. Bowling, Gregory M. Cooper, Brittney H. Davis, Kelly M. East, Candice R. Finnila, Blake Goff, Susan Hiatt, Melissa Kelly, Whitley V. Kelley, Bruce R. Korf, Donald R. Latner, James Lawlor, Thomas May, Matt Might, Irene P. Moss, Mariko Nakano-Okuno, Tiffany Osborne, Stephen Sodeke, Adriana Stout, Michelle L. Thompson
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- Journal:
- Journal of Clinical and Translational Science / Volume 7 / Issue s1 / April 2023
- Published online by Cambridge University Press:
- 24 April 2023, pp. 100-101
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OBJECTIVES/GOALS: Supported by the State of Alabama, the Alabama Genomic Health Initiative (AGHI) is aimed at preventing and treating common conditions with a genetic basis. This joint UAB Medicine-HudsonAlpha Institute for Biotechnology effort provides genomic testing, interpretation, and counseling free of charge to residents in each of Alabama’s 67 counties. METHODS/STUDY POPULATION: Launched in 2017, as a state-wide population cohort, AGHI (1.0) enrolled 6,331 Alabamians and returned individual risk of disease(s) related to the ACMG SF v2.0 medically actionable genes. In 2021, the cohort was expanded to include a primary care cohort. AGHI (2.0) has enrolled 750 primary care patients, returning individual risk of disease(s) related to the ACMG SF v3.1 gene list and pre-emptive pharmacogenetics (PGx) to guide medication therapy. Genotyping is done on the Illumina Global Diversity Array with Sanger sequencing to confirm likely pathogenic / pathogenic variants in medically actionable genes and CYP2D6 copy number variants using Taqman assays, resulting in a CLIA-grade report. Disease risk results are returned by genetic counselors and Pharmacogenetics results are returned by Pharmacists. RESULTS/ANTICIPATED RESULTS: We have engaged a statewide community (>7000 participants), returning 94 disease risk genetic reports and 500 PGx reports. Disease risk reports include increased predisposition to cancers (n=38), cardiac diseases (n=33), metabolic (n=12), other (n=11). 100% of participants harbor an actionable PGx variant, 70% are on medication with PGx guidance, 48% harbor PGx variants and are taking medications affected. In 10% of participants, pharmacists sent an active alert to the provider to consider/ recommend alternative medication. Most commonly impacted medications included antidepressants, NSAIDS, proton-pump inhibitors and tramadol. To enable the EMR integration of genomic information, we have developed an automated transfer of reports into the EMR with Genetics Reports and PGx reports viewable in Cerner. DISCUSSION/SIGNIFICANCE: We share our experience on pre-emptive implementation of genetic risk and pharmacogenetic actionability at a population and clinic level. Both patients and providers are actively engaged, providing feedback to refine the return of results. Real time alerts with guidance at the time of prescription are needed to ensure future actionability and value.
Lessons learned about harmonizing survey measures for the CSER consortium
- Katrina A.B. Goddard, Frank A.N. Angelo, Sara L. Ackerman, Jonathan S. Berg, Barbara B. Biesecker, Maria I. Danila, Kelly M. East, Lucia A. Hindorff, Carol R. Horowitz, Jessica Ezzell Hunter, Galen Joseph, Sara J. Knight, Amy McGuire, Kristin R. Muessig, Jeffrey Ou, Simon Outram, Elizabeth J. Rahn, Michelle A. Ramos, Christine Rini, Jill O. Robinson, Hadley Stevens Smith, Margaret Waltz, Sandra Soo-Jin Lee
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- Journal:
- Journal of Clinical and Translational Science / Volume 4 / Issue 6 / December 2020
- Published online by Cambridge University Press:
- 24 April 2020, pp. 537-546
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Introduction:
Implementation of genome-scale sequencing in clinical care has significant challenges: the technology is highly dimensional with many kinds of potential results, results interpretation and delivery require expertise and coordination across multiple medical specialties, clinical utility may be uncertain, and there may be broader familial or societal implications beyond the individual participant. Transdisciplinary consortia and collaborative team science are well poised to address these challenges. However, understanding the complex web of organizational, institutional, physical, environmental, technologic, and other political and societal factors that influence the effectiveness of consortia is understudied. We describe our experience working in the Clinical Sequencing Evidence-Generating Research (CSER) consortium, a multi-institutional translational genomics consortium.
Methods:A key aspect of the CSER consortium was the juxtaposition of site-specific measures with the need to identify consensus measures related to clinical utility and to create a core set of harmonized measures. During this harmonization process, we sought to minimize participant burden, accommodate project-specific choices, and use validated measures that allow data sharing.
Results:Identifying platforms to ensure swift communication between teams and management of materials and data were essential to our harmonization efforts. Funding agencies can help consortia by clarifying key study design elements across projects during the proposal preparation phase and by providing a framework for data sharing data across participating projects.
Conclusions:In summary, time and resources must be devoted to developing and implementing collaborative practices as preparatory work at the beginning of project timelines to improve the effectiveness of research consortia.