Why Aren’t Genomic Screening Programs Standard in Healthcare Yet?
Twenty years have passed since the completion of the Human Genome Project, and still very few healthcare systems broadly use genomic screening for assessing individual health risk across their entire patient populations. Most only use genomic screening for predictive, carrier, or diagnostic testing in a small subset of patients based on a person’s symptoms or family history. However, the results of comprehensive genomic screening can provide valuable information for many more individuals and their family members. This enables their healthcare providers to offer individualized preventative care and treatments.
Genomic screening examines the complete set of DNA that makes up an individual’s genetic makeup for variations that may increase their risk for rare genetic disorders or common diseases, such as heart disease or cancer. For example, familial hypercholesterolemia (FH) affects approximately 1 in 200 individuals, but less than 10% of those individuals have been diagnosed and appropriately treated to prevent heart failure. Most individuals with FH have a variant in one of three genes that genomic screening tests can easily detect. This greatly impacts their future care and the care of their at-risk family members.
Several innovative healthcare systems, including Geisinger, AdventHealth, and NorthShore, have pioneered community-wide genomic screening programs in primary and specialty care to proactively prevent and detect diseases like FH at an early stage when they are most treatable. These screening programs typically limit the number of diseases that they report genetic variants in to those that have been defined by the Centers for Disease Control and Prevention (CDC) as “Tier 1 Genomics Applications.” These are conditions that have significant potential for a positive impact on public health based on available evidence-based guidelines and recommendations. Some also interrogate pharmacogenetic variants that influence drug selection and dosage, or the approximately 70 genes on the American College of Medical Genetics and Genomics (ACMG) Secondary Findings List. These are genes recommended to be reported if pathogenic variants are identified incidentally as part of a diagnostic exome or genome test.
Even with this expanded reporting, it is important to note that the sequencing method that underlies most genomic screening programs is, in fact, exome or genome sequencing. This provides an incredible untapped opportunity to detect and clinically report genetic variants that are causative of thousands of rare diseases, generate dozens of different polygenic risk scores, predict drug response, and identify health traits.
The last two decades have seen dramatically lowered DNA sequencing costs that sparked a revolution in clinical genomics and concurrently increased the field’s understanding of gene-disease relationships. The cost of sequencing the first human genome as part of the Human Genome Project is estimated to have been ~2.7 billion dollars, while recent technological advances have reduced the cost to as little as $200. Thus, while the cost of genetic testing was historically high, the costs have substantially decreased to within the same realm of many other routinely ordered diagnostic tests.
If genomic screening is now affordable, then why isn’t genomic screening used routinely to inform health care today? Remaining barriers to the implementation of large-scale, community-wide genomic screening programs include:
- The familiarity and comfort of clinicians with understanding and acting upon genetic test results
- Limited time available to clinicians to spend interpreting test results and educating patients and family members
- Integration of various systems and providing access to genetic information to clinicians, storage and analysis of genetic information, and integration of genetic information with health records and patient data streams
LifeOmic has developed a comprehensive solution, the LifeOmic Platform, to tackle these barriers and enhance accessibility to precision medicine for large-scale genomic screening initiatives. By integrating clinical and -omics data from diverse sources, such as electronic health records and laboratories, the LifeOmic Platform offers a complete overview of an individual’s health and provides valuable insights for entire populations. Additionally, the platform features a customizable mobile application that delivers clinician and patient education programs, collects patient-reported outcomes and biometrics, and employs a chatbot with machine learning to streamline communication with the patient’s care team. Through the LifeOmic Platform, we’re building a future where clinicians will readily have a complete picture of their patients, including genomic screening results, to improve healthcare.
References
- NorthShore Genomic Research Program. https://www.northshore.org/personalized-medicine/research-innovation/genomic-health-initiative/. Accessed 16 Mar 2023.
- AdventHealth WholeMe. https://www.adventhealthresearchinstitute.com/research/whole-person/clinical-trials/wholeme. Accessed 16 Mar 2023.
- Geisinger MyCode. https://www.geisinger.org/precision-health/mycode. Accessed 16 Mar 2023.
- Sturm, A. C. et al. Clinical Genetic Testing for Familial Hypercholesterolemia: JACC Scientific Expert Panel. J Am Coll Cardiol 72, 662–680 (2018). https://doi.org/10.1016/j.jacc.2018.05.044
- Babbi, G. et al. eDGAR: a database of Disease-Gene Associations with annotated Relationships among genes. BMC Genomics 18, 554 (2017). https://doi.org/10.1186/s12864-017-3911-3
- Haverfield, E. V. et al. Physician-directed genetic screening to evaluate personal risk for medically actionable disorders: a large multi-center cohort study. BMC Med 19, 199 (2021). https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-021-01999-2
- Schmidlen, T. et al. Use of a chatbot to increase uptake of cascade genetic testing. Journal of Genetic Counseling 31, 1219–1230 (2022). https://doi.org/10.1002/jgc4.1592
- Heald, B. et al. Using chatbots to screen for heritable cancer syndromes in patients undergoing routine colonoscopy. J Med Genet 58, 807–814 (2021). http://dx.doi.org/10.1136/jmedgenet-2020-107294
- Ponathil, A., Ozkan, F., Welch, B., Bertrand, J. & Chalil Madathil, K. Family health history collected by virtual conversational agents: An empirical study to investigate the efficacy of this approach. J Genet Couns 29, 1081–1092 (2020). https://doi.org/10.1002/jgc4.1239
- UPenn Effort Organizes, Integrates Genetic Testing Results in Electronic Health Records. GenomeWeb. https://www.genomeweb.com/informatics/upenn-effort-organizes-integrates-genetic-testing-results-electronic-health-records. Accessed 16 Mar 2023.
- Acosta, J. N., Falcone, G. J., Rajpurkar, P. & Topol, E. J. Multimodal biomedical AI. Nat Med 28, 1773–1784 (2022). https://www.nature.com/articles/s41591-022-01981-2
- The Cost of Sequencing a Human Genome. https://www.genome.gov/about-genomics/fact-sheets/Sequencing-Human-Genome-cost. Accessed 30 March 2023.
- Element Delivers $200 Genome on AVITI™ Benchtop Sequencing System. https://www.elementbiosciences.com/200-dollar-genome. Accessed 30 March 2023.
- PennChart Genomics Initiative. https://www.med.upenn.edu/pgi/. Accessed 30 March 2023.
- ACMG Recommendations for Reporting of Incidental Findings in Clinical Exome and Genome Sequencing. https://www.ncbi.nlm.nih.gov/clinvar/docs/acmg/. Accessed 30 March 2023.