We recently interviewed Premal Shah, Ph.D., CEO of MyOme, a precision health company providing whole‑genome sequencing testing for proactive risk assessments, alongside clinical diagnostics offerings. See the full transcript below.

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1) To start, Premal, could you share your background in precision medicine and your role at MyOme?

I’m currently CEO at MyOme, a precision health company applying whole‑genome sequencing and analysis within personalized preventive care and in clinical diagnostic contexts. Before this, I helped build Ciitizen, which focused on patient access to medical records; alongside genetics, these remain the most consequential categories of personal health data, and the goal was to enable agency and careful stewardship. My career has centered on scaling technologies that translate high‑quality biological data into practical insights for patients and providers, with an emphasis on rigorous validation and transparent communication. The overarching aim at MyOme is to make the whole genome clinically useful across two settings: proactive risk assessment for generally healthy individuals, and diagnostic applications when a disease is suspected or already identified, so that genetic contributors can be clarified.

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2) How do proactive or risk-assessment versus clinical genomic testing differ in how results are used, and why is there a need for both? What distinct technologies underpin each approach?

Proactive genomic testing aims to characterize risk before symptoms, supporting earlier detection and potential delay of disease onset; even partial adherence to prevention or surveillance can translate to significant system and national‑level savings due to avoided complications and earlier interventions. In this setting, the utility often comes from broader risk stratification across common diseases, with results used to inform lifestyle counseling, screening intervals, and shared decision‑making rather than to diagnose a specific condition.

Clinical diagnostic testing is performed when there is a suspected disorder, with results directly impacting differential diagnosis, confirmatory testing, and care plans. In rare disease diagnostics, only about 40–50% of children with developmental delay receive a genetic diagnosis using conventional approaches, which historically have relied on exome sequencing at high volume. Whole‑genome sequencing can add value by capturing variants beyond exome reach, and there are published case examples–and with our Rare Disease test–where individuals underwent multiple standard tests without a finding but later received a genetic diagnosis through genome‑based evaluation; while a genetic answer is not itself a treatment, it can connect families with relevant communities, clinical trials, and management guidelines. The technical distinction matters: a genome‑based approach can detect structural variants, tandem repeat expansions, mitochondrial findings, and other variant classes that may be missed by exome alone, thereby expanding the scope of potential explanations when disease is present.

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3) How are variants of unknown significance typically handled?

In general, it is good to be careful about uncertainty, especially in proactive health settings, because it can cause unnecessary anxiety, whereas in diagnostic contexts, uncertainty can still be informative. We also recognize that many people need guidance, and that’s what genetic counselors provide, a support system for patients and clinicians through that process. If a VUS (variant of unknown significance) is later reclassified as clinically significant, we at MyOme will update an issued report and recontact the physician to share the new information.

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4) Could you outline today’s comprehensive genomic testing landscape—clinical and proactive or risk assessment—and what technologies underpin each approach? Which specialists are involved in which use case?

Let’s start with diagnostics. The current paradigm includes targeted panels and exome and whole‑genome sequencing to identify high‑impact variants—SNVs, CNVs, and structural variants. As mentioned, a whole‑genome‑based approach has advantages over narrower methods.

One area we’ve researched for years is long‑read sequencing. Short‑read sequencing on Illumina machines provides strong coverage for many variants but often struggles with large structural variants. From a bioinformatics standpoint, we can detect many structural variants from short reads computationally, but in diagnostics, you don’t want to rely solely on inference.

So we implemented long‑read sequencing in the latest version of our rare disease product a couple of months ago. When genome analysis indicates a structural variant or a tandem repeat expansion, we automatically reflex to confirm with long reads. That confirmatory step is valuable. For example, we evaluate 20 tandem repeat expansions; some peers evaluate 15 or 16. The difference matters when medical geneticists are searching for a needle in a haystack. As a technology‑first company, we aim to move beyond the current 40–50% diagnostic yield and push it higher to get more children diagnosed.

In terms of specialists, medical geneticists and developmental pediatricians are primary users. With new American Academy of Pediatrics (AAP) guidelines, some pediatricians have begun ordering tests; they often need added support, and they value that.

Another advantage of a genome‑based approach is flexibility. Today, the process often starts with Fragile X testing, which is usually negative because prevalence is under 1%. Then comes copy‑number analysis via microarray, with a 10–15% diagnostic yield. Then exome sequencing. Each step introduces delays, prior authorizations, and out‑of‑pocket costs. With a genome‑first approach, if copy‑number analysis is negative, you can immediately reflex to exome‑level analysis, and similarly reflex up to genome‑level analysis without starting over. That’s the power of analyzing the whole genome.

On the proactive health side, the field is changing quickly. Historically, genomics for proactive health was panel‑based as companies offered 250‑gene or 300‑gene panels. The issue is that among people with a family history, only about 5–7% receive a single‑gene result. For example, someone with a family history of breast cancer may go from ~12% average lifetime risk to ~24%, which is a doubling of risk, leading many to assume a single‑gene condition like BRCA. Yet even among women with a family history, only 5–6% have a single‑gene cause. The remaining elevated risk likely reflects genome‑wide factors; that’s where polygenic risk scores matter.

Panel‑only approaches are limited for understanding risk and for return on investment (ROI) in health systems or employer programs. With polygenic risk scoring and integrated risk models, everyone receives risk information, not just those with rare, high‑penetrance variants, across common diseases like coronary artery disease, diabetes, and cancers. We integrate clinical factors and train and validate across diverse ancestries, including mixed ancestry. The core technology is whole‑genome sequencing.

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5) What are the current gaps or unmet needs in proactive or risk assessment genomic testing broadly?

Historically, the genomics market had two tracks. Recreational genomics (e.g., 23andMe, Ancestry) focused on ancestry; their health efforts struggled, in part because array technology captures a small fraction of the genome. Meanwhile, clinical panel providers (e.g., Invitae) expanded to 200–300 gene panels for proactive assessment, but most individuals still received limited risk insight. The field has shifted to genome‑based methods that support broader risk characterization, including polygenic risk.

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6) What challenges arise when interpreting genetic results for people from diverse backgrounds, and how should they be addressed?

Most reference data are Eurocentric, which can lead to variant misclassification and less accurate polygenic risk scores in diverse populations. The UK Biobank, a common standard, is about 96–97% European. To address this, we invest in and use diverse, multiethnic reference datasets for different indications and develop ancestry‑aware algorithms to calibrate polygenic scores across populations, including mixed ancestry. Transparency about model limitations and clinician education is essential. Community engagement and equitable data governance help build trust. A program with Catalyst in Alabama illustrates a statewide population health initiative emphasizing primary care engagement in a high‑risk population, involving Southern Research and the University of Alabama.

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7) Proactive genome testing and broader direct-to-consumer sequencing face questions on data security; what are the key challenges and the most effective ways to mitigate them?

From a technical standpoint, data should be protected with appropriate encryption and storage practices, and the approach is publicly described. In terms of usage, test data may be used without additional explicit consent only to improve internal tests, not for sale or external sharing. Any broader use would require re‑consent. Clear, transparent consent processes, not blanket, fine‑print permissions, are important for trust. At MyOme, all data resides on the MyOme platform; many employees, including those who have taken the MyOme test, have their data handled the same way.

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8) Broadly, how are we equipped to handle the depth of information that you get from whole genome sequencing?

For proactive testing, we can curate our gene list based on actionability, prevalence, and penetrance, recognizing that having a variant does not guarantee disease. Genetic counselors regularly evaluate inclusion criteria so physicians see clinically meaningful findings. Although we sequence every gene, reporting can be scoped; for example, some clinicians prefer a focused set of cardiac genes rather than the full list. That flexibility is a benefit of a genome‑based approach.

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9) How do payer policies toward comprehensive genomic testing look today, and in what ways do they encourage or discourage uptake of direct‑to‑consumer offerings?

Payer policy in the United States, genomics included, often does not align well with patient care and innovation. Preventive genomics has been discussed for years, but remains limited in reimbursement. Our proactive health test is not reimbursed currently. For now, payment is out‑of‑pocket, but prices have decreased. For most employers, we offer sub‑$400 genome analysis; for concierge practices, the premium MyOme Health Plus package is more. Compared to some other screening products priced around $900 annually, these options are increasingly accessible. Many stakeholders see value in population‑wide risk information rather than focusing on the small minority with single‑gene findings. 

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10) Where is the adoption of comprehensive genomic testing, especially whole‑genome sequencing, today, and how do you expect it to evolve in the near term?

The United States has historically been conservative and methodical in adoption, but momentum is building. Genome-based testing in the Rare Disease context is likely to expand given recent guideline updates and expanding payor coverage. Proactive health represents a significant opportunity if risk can be assessed broadly and interventions implemented effectively.

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11) Looking ahead five years, how will accessibility to comprehensive genomic testing change, and what developments would most accelerate uptake?

Sequencing costs have fallen over the past decade, while bioinformatics (polygenic risk scores and integrated models) has improved the relevance of results. Those trends suggest much broader access to genome sequencing in the next five years. Prices may continue to decline, but the focus is on delivering information that meaningfully informs individual risk.

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