3 ways to overcome information overload from genetic testing
As labs take advantage of new ways to guide care using data, their power multiplies. They are opening possibilities to maintain wellness, target therapies and create value. Their data and knowledge make them invaluable—and this is just the beginning.
But does more data always mean more power?
With the rise of genetic testing, the lab has more data than they can possibly handle. And with the promise of leveraging this data more and more into the future, genetic testing is not slowing down.
Yet with little ability to transform genetic data into actionable insights, laboratorians are often left feeling less empowered and more overloaded. To speed diagnosis and optimize utilization of genetic tests, they first have to begin to make better sense of their information. They need to overcome information overload.
Here are the top three ways to make this a reality.
Contributing Lab Leaders
Pathology Department Chairman
University of Texas Medical Branch at Galveston
Kenneth Bloom, Ph.D.
Head of Oncology and Immunotherapy
Human Longevity Inc.
When NOT to use whole genome sequencing
By Michael Laposata
When trying to pinpoint a specific genetic issue, whole genome sequencing is not a perfect fit. This method would require the lab to reconstitute all of the patient’s DNA and run the sequence many times to uncover the answer.
Acute myeloid leukemia
Gene targeting approach
Provided only the relevant information
Evaluated which genes are mutated in the tumor
Identified 53 relevant genes to test in a targeted panel
Guiding the course of care
Determined severity of cancer and chemotherapy approach without information overload
1. Choose tests that give the right information, not the most information
Whole genome sequencing offers some incredible benefits, yet may not always be the best testing approach.
According to Kenneth Bloom, Ph.D., “We understand 1% of the total genome—max. Whole genome sequencing takes much more time and resources, and we’re incredibly limited with what we can do with the information. In many cases, it can offer care-changing insights, but we need to be thoughtful about when to use it. “
Overcome information overload with a more targeted testing approach
Simple lab test
Many common genetic disorders don’t require genetic sequencing at all. Before taking excessive action, see if there is a lab test that can give you all the answers you need.
Sometimes, you don’t need to test for every gene, but only a handful. If you determine that a particular cancer, for example, only affects a targeted set, a gene panel can be all you need to guide the course of care.
Genetic mutation analysis
If you’re looking for a specific mutation within a gene, a genetic test may be all you need. As with gene panels, start by identifying the disorder, deduce which genes are implicated, then perform targeted genetic tests to look for common mutations in those genes. This method is commonly used in matters related to family history.
2. Search outside your lab, and also within it
Despite the knowledge of anyone in your network, sometimes the answer lies beyond. And sometimes, it’s right under your nose. So when you’re treading in a sea of data and looking for direction, just get searching.
Overcome information overload by knowing where to look
Search for an expert
Whether a health care professional or not, a genetics expert may hold the key to your most challenging questions. Look far and wide for this person and connect by any means. Your patients’ lives could be at stake.
Search within your data
Forward-thinking lab leaders, like Kenneth Bloom, have built tools to help make sense of their data. Here are two amazing examples of what they can do.
Example 1: Real-time genome queries
Commercial databases, such as Bloom’s HLI search tool, function like Google for genetic data. His team can input questions like, “How often do we see [this particular] genome as it pertains to a disease?” This has done wonders to help HLI sift through data, inform care, and avoid information overload.
Example 2: Redefining a trio analysis
If a patient has a syndrome that can’t be identified, a genomic database search tool can help rule out syndromes that their parents don’t have or carry. Bloom’s tool can do this by taking a baby’s genome, then subtracting the mother’s and the father’s genomes. While this can take months with a traditional trio analysis, this tool can do it in seconds. Users can then refine the results further with a keyword analysis.
Search the literature
Considering how little we actually know about the human genome, you may find yourself looking for an answer that has yet to be uncovered. Laposata recommends doing a weekly literature search on relevant topics. When someone somewhere gets a lead, you will too.
3. Work better and smarter—together
No matter how much any individual knows, it is only a fraction of what your network collectively knows. Don’t go it alone. Bring leading minds together and collaborate to make sense of the unknown.
Overcome information overload by leveraging your collective wisdom
Diagnostic management teams (DMTs)
For any case, assemble a team of the brightest minds to contribute their knowledge. Include experts such as anatomic pathologists, geneticists, specialists from across departments and critical care—and perhaps even the patient and family. This enables you to optimize not only patient outcomes, but your ability to manage volumes of information.
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