Healthcare magazine for research scientists, labs, pathologists, hospitals, cancer centers, physicians and biopharma companies providing news articles, expert interviews and videos about molecular diagnostics in precision medicine
Issue link: https://clinicalomics.epubxp.com/i/853204
www.clinicalomics.com July/August 2017 Clinical OMICs 13 As a molecular biologist, what are some of the biggest challenges you encounter running a clinical lab? Heidi Rehm: The biggest challenge we encounter is whether we can accurately identify and interpret the causes of a disease in an individual, and give an accurate answer that those patients can act on in a safe and appropriate way to improve their health. It is not straightforward to interpret genetic information in an informative way. The challenge is to do the best you can, knowing the best you can is not always perfect. Is there a consensus in success rates in identifying a causal variant in an undiagnosed patient? HR: There are two layers to that question. One is a question of technical validity. Can we physically detect a variant that may be causative for a patient based on the technol- ogy? The more challenging variants can be difficult to detect, so we can technically miss a variant even when it is in a region that we claim to be looking at: the exome, the entire coding region of the genome. So we don't know what we don't know. That is, we don't always know what the limitations of our technol- ogy are and we can't assess what it is we are missing other than to simply say that there are limitations to the technology. We generally understand those limitations, but we don't have a quantitative way to say we are miss- ing 5% of these or 10% of those. To some extent, when we validate a test we put in known mutations and we can assess the things that are known that we are looking for that we have missed. But we can't do that comprehen- sively enough, with enough variety, and with enough variations to assess the most challenging aspects. What about the other layer? HR: I published a review in Nature Genetics recently and I showed a table of typical detection rates for typical genetic disorders and indications. The gist of that was on average, we detect about 25% of the causes of disease in patients who undergo genetic testing. You can argue that we are missing 75% and the question then is: What is the basis for missing that 75%? It spans four major areas: One is the patient doesn't have a genetic disease, and no matter how good we are we will never find it because their disease is not genetic. That is some unknown percentage. The second is we are doing an exome and the answer to this question is in the noncod- ing regions, so we are going to miss it using this tech- nique—it was the wrong test was run. Third, even if we are looking in the right places, we technically miss the right variation for the reasons we just talked about, because we can't detect structural variations or other things as well as we'd like. And fourth, we got the variant but we weren't able to understand or interpret it, such that we missed the interpretation of the variants. So it is there among the bucket of 5 million variants in the genome, or 20,000 to 50,000 variants in the exome, but we simply couldn't identify which was the right one. Those are the reasons we have, on average, 75% of cases that are negative. Clinical genomics thought leader shares her insights on exome vs. genome sequencing, data-sharing initiatives, and more "It is not straight- forward to interpret genetic information in an informative way. The challenge is to do the best you can, knowing the best you can is not always perfect." (continued on next page)