Tag: Genomics

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Remembering J. Craig Venter, PhD

J. Craig Venter, PhD recently passed away at the age of 79 from complications following a cancer diagnosis. He was well known in both science and industry and was an integral part of sequencing the human genome in the late 90s, competing with the government organized Human Genome Project. Throughout his career, he made many other important contributions in microbiology, with the “minimal cell,” in synthetic biology, and in personalized medicine. GEN editors share anecdotes of their experiences with him, reflect on the impact that his work has had on various fields in biology, in biotech, and in how the world has responded to the disruptions caused by Venter.

Listed below are links to the GEN stories referenced in this episode of Touching Base:

Genomics Pioneer and Life Sciences Entrepreneur J. Craig Venter Dies at 79
GEN, April 30, 2026

J. Craig Venter Describes a Human Genomics Revolution Still In Progress
By J. Craig Venter, PhD, GEN, June 13, 2025

Lessons from the Minimal Cell
By Hana El-Samad, PhD, GEN, August 21, 2023

From Sequencing to Sailing: Three Decades of Adventure with Craig Venter
By Fay Lin, PhD, GEN, March 8, 2023

“Cracking the Genome”
By Kevin Davies, PhD

Touching Base Podcast
Hosted by Corinna Singleman, PhD

Behind the Breakthroughs
Hosted by Jonathan D. Grinstein, PhD

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Gene Therapy Briefs: Regeneron Wins FDA Approval for First Neurosensory Gene Therapy

The FDA has granted accelerated approval to Regeneron Pharmaceuticals’ Otarmeni™ (lunsotogene parvec-cwha) as the first gene therapy designed to restore a neurosensory function to normal levels.

Otarmeni is an adeno-associated virus vector-based gene therapy indicated for treating children and adults with severe-to-profound and profound sensorineural hearing loss, defined as any frequency >90 decibel hearing level [dB HL], associated with molecularly confirmed biallelic variants in the OTOF gene, preserved outer hair cell function, and no prior cochlear implant in the same ear.

Otarmeni (formerly DB-OTO) is the first and only in vivo gene therapy indicated for OTOF-related hearing loss. Regeneron said it will make Otarmeni available for free in the U.S.

The FDA based its accelerated approval decision on the improvement of hearing sensitivity as measured by average pure tone audiometry (PTA) at week 24 during the Phase I/II CHORD trial (NCT05788536). Twenty participants ages 10 months to 16 years received a single dose of Otarmeni via intracochlear infusion—10 patients in one ear, the other 10 in both ears. Data from CHORD showed:

  • 80% of participants (16 of 20) reported hearing improvements per pure tone audiometry assessments at ≤70 dB HL at 24 weeks, achieving the trial’s primary endpoint, while one additional participant achieved the threshold by week 48.
  • 70% (14 of 20) showed an auditory brainstem response (ABR) at ≤90 decibels at 24 weeks, achieving the trial’s key secondary endpoint.
  • Among participants followed to 48 weeks, all prior responders maintained a response to therapy, and 42% of all participants (five of 12) achieved normal hearing that included whispers (≤25 dB HL).

“This unprecedented breakthrough in gene therapy has already proven to be life-changing for many of the children in our clinical trial and their families,” said George D. Yancopoulos, MD, PhD, board co-chair, president and chief scientific officer of Regeneron. 1

The FDA said its accelerated approval may hinge upon verification and description of clinical benefit in the confirmatory portion of the CHOIRD trial, a first-in-human, multicenter, open-label trial designed to assess the safety, tolerability and preliminary efficacy of DB-OTO in infants, children, and adolescents with otoferlin variants.

Otarmeni is the first gene therapy, and second new molecular entity, to win FDA approval under the agency’s Commissioner’s National Priority Voucher (CNPV) pilot program.

Launched in October by FDA Commissioner Martin A. Makary, MD, CNPV awards vouchers to drug developers whose work is deemed to address a health crisis in the U.S., deliver more innovative cures, address unmet public health needs, and increase domestic drug manufacturing as a national security issue. The vouchers entitle companies to reviews of their final applications within a target timeframe of 1–2 months rather than the standard 10–12 months.

Intellia’s Lonvo-Z begins rolling BLA following positive Phase III data

Intellia Therapeutics has launched a rolling Biologics License Application (BLA) submission to the FDA seeking regulatory approval of lonvoguran ziclumeran (lonvo-z), after announcing positive topline results from the global Phase III HAELO trial (NCT06634420) in hereditary angioedema (HAE)—the first Phase III data reported for an in vivo gene editing therapy.

HAELO is a randomized, double-blind, placebo-controlled Phase III trial designed to evaluate the efficacy and safety of a one-time 50 mg dose of lonvo-z in adults and adolescents aged 16 years and older with Type I or Type II HAE. The trial’s key endpoints focused on the number of HAE attacks experienced by patients, quality of life, safety and tolerability. Eighty patients were enrolled with 52 receiving lonvo-z and 28, placebo.

HAELO met its primary endpoint. For the six-month efficacy evaluation period (weeks 5 to 28), a one-time infusion of lonvo-z reduced attacks by 87% vs. placebo, with a mean monthly attack rate of 0.26 in the lonvo-z arm vs. 2.10 in the placebo arm.

Other key findings from HAELO:

  • The trial met all key secondary endpoints with statistical significance (p<0.0001). These included a 62% rate of patients who were entirely attack free and therapy free in the lonvo-z arm for the six-month efficacy evaluation period, vs. 11% of patients in the placebo arm.
  • Lonvo-z showed favorable safety and tolerability data. The most common treatment emergent adverse events (TEAEs) during the primary observation period (infusion through week 28) were infusion-related reactions, headache and fatigue. All TEAEs reported as of the data cutoff (February 10, 2026) were mild or moderate, with no serious adverse events observed in the lonvo-z arm.
  • As of the data cutoff, all patients who received lonvo-z at baseline or in crossover after week 28 remained long-term prophylaxis (LTP) free.

“Today’s HAELO results represent a profound milestone for Intellia, the broader CRISPR and precision medicine fields and, most importantly, the HAE community,” said John Leonard, MD, Intellia’s president and CEO. “These data affirm lonvo-z’s potential, with one dose, to offer prolonged freedom from both attacks and the need for ongoing therapy.” 2

Intellia said researchers plan to present additional clinical data from HAELO at the 2026 European Academy of Allergy and Clinical Immunology Congress (EAACI), set for June 12-15 in Istanbul, Turkey (Abstract #100217).

Lonvo-z is designed to inactivate the kallikrein B1 (KLKB1) gene in order to permanently lower kallikrein and bradykinin levels. Lonvo-z is designed as a one-time treatment that is administered in an outpatient setting.

Intellia said it is preparing for a potential U.S. launch of lonvo-z in the first half of 2027.

J. Craig Venter Dies: Pioneer in gene discovery, genomics, and synthetic biology

Craig Venter, PhD, a pioneer in gene discovery, human genomics, and synthetic biology, died April 29 in San Diego after a brief hospitalization for unexpected side effects that arose from treatment of recently diagnosed cancer. He was 79.

Venter was founder, board chair, and CEO of the institute that bears his name in La Jolla, CA. Earlier at the National Institutes of Health (NIH), he helped pioneer gene discovery using expressed sequence tags (ESTs), enabling rapid identification of large numbers of human genes and accelerating genome mapping efforts.

He went on to lead efforts that produced the first draft sequences of the human genome. He and colleagues later published the first high-quality diploid human genome, a scientific milestone that demonstrated the importance of capturing genetic variation inherited from both parents.

Venter’s work helped define and advance modern genomics, as well as launched the field of synthetic biology, where he and his teams constructed the first self-replicating bacterial cell controlled by a chemically synthesized genome—proof that genomes could be designed digitally, built from chemical components, and like a computer, booted up to run a living cell.

Through the Sorcerer II Global Ocean Sampling Expedition, Venter and his teams used metagenomics to reveal microbial diversity, reporting the discovery of millions of new genes and expanding the known universe of protein families—work that added to knowledge and insight of the ocean microbiome and its role in planetary systems.

“Venter was controversial and often challenged the scientific orthodoxy, with critics accusing him of hype and going overboard on privatization,” said John Sterling, Editor in Chief of Genetic Engineering & Biotechnology News, who has known and worked editorially with Venter over the past 35 years. “To many, he was a visionary focusing on technological acceleration and blending academic science with the zeal of an entrepreneur. Supporters saw him as a pioneer who sped up genomics by years.” 3

In addition to founding the J. Craig Venter Institute (JCVI), Venter was a serial entrepreneur who co-founded Synthetic Genomics, Human Longevity, and most recently Diploid Genomics, advancing efforts designed to translate genomics and synthetic biology into tools for health and society.

He was also a fierce advocate for robust federal science funding, as well as for partnerships that accelerate progress across government, academia, and industry.

“Craig believed that science moves forward when people are willing to think differently, move decisively, and build what doesn’t yet exist,” said Anders Dale, president of JCVI. “His leadership and vision reshaped genomics and helped ignite synthetic biology. We will honor his legacy by continuing the mission he built—advancing genomic science, championing the public investments that make discovery possible, and partnering broadly to turn knowledge into impact.” 4

Rocket Pharma selling Priority Review Voucher for Kresladi™ for $180M

Rocket Pharmaceuticals has agreed to sell for $180 million the Rare Pediatric Disease Priority Review Voucher (PRV) it was awarded by the FDA after the agency granted accelerated approval of Kresladi™ (marnetegragene autotemcel).

Kresladi is an autologous hematopoietic stem cell-based gene therapy indicated to treat children with severe leukocyte adhesion deficiency-I (LAD-I) due to biallelic variants in ITGB2 without an available human leukocyte antigen-matched sibling donor for allogeneic hematopoietic stem cell transplant.

The indication was approved in March under accelerated approval based on increase in neutrophil CD18 and CD11a surface expression. The accelerated approval of Kresladi is subject to confirmation of its clinical benefit, to be based on an evaluation of longer-term follow-up data of treated patients in the ongoing Phase I/II trial (NCT03812263) and through a post-marketing registry. The study generated positive topline data showing 100% overall survival at 12 months post-infusion (and for the entire duration of follow-up) for all nine LAD-I patients with 18 to 42 months of available follow-up.

The accelerated approval followed a resubmission of Rocket’s Biologics License Application for Kresladi. The original submission was rejected by the FDA in 2024 through a Complete Response Letter that requested additional Chemistry, Manufacturing, and Controls (CMC) information, but did not raise safety or efficacy issues about the gene therapy.

Rocket said it plans to use proceeds from the PRV sale toward advancing its prioritized cardiovascular gene therapy pipeline, including clinical-stage programs in Danon disease, PKP2-associated arrhythmogenic cardiomyopathy (PKP2-ACM), and BAG3-associated dilated cardiomyopathy (BAG3-DCM).

“The monetization of our PRV, following the FDA approval of Kresladi, provides meaningful non-dilutive capital and extends our cash runway into the second quarter of 2028,” said Gaurav Shah, MD, Rocket Pharmaceuticals CEO. “This strengthens our ability to advance key clinical milestones across our cardiovascular gene therapy pipeline, with all programs on track.” 5

Passage Bio cuts staff 75%, launches strategic review

Passage Bio said it will eliminate 75% of its staff in a cost-cutting restructuring that is part of the company’s effort to review strategic alternatives.

“The Company expects that the aggregate severance and exit costs for the Restructuring Plan will be approximately $3.3 million, which will be recorded primarily in the second quarter of 2026,” Passage Bio said in a regulatory filing. 6

Passage Bio has said it plans to review strategic alternatives that may include merger or acquisition transactions, a reverse merger, a sale of assets of the company, strategic partnerships, licensing opportunities, or other potential paths.

The restructuring followed Passage Bio receiving feedback during a Type C meeting with officials at the FDA that indicated that the company will be required to complete a randomized controlled registrational trial evaluating its lead pipeline candidate PBFT02 as a treatment for frontotemporal dementia (FTD) with granulin (GRN) mutations.

PBFT02 is a gene replacement therapy that uses an adeno-associated virus serotype 1 (AAV1) viral vector to deliver, through intra cisterna magna (ICM) administration, a functional GRN gene that encodes the progranulin protein (PGRN).

The 75% workforce cut amounts to approximately 18 people, based on the 24 full-time employees it reported as of December 31, 2025, according to its annual report.

LEO Pharma acquires Replay for $50M upfront, milestones

LEO Pharma has agreed to acquire Replay, a developer of gene therapies for rare genetic dermatological conditions, in a deal that the buyer said will add deep expertise and a next-generation gene therapy platform to its pipeline, namely Replay’s high‑payload herpes simplex virus (HSV) delivery vector.

LEO Pharma plans to acquire Replay for $50 million upfront, plus milestone payments and tiered single-digit royalties.

Replay’s gene therapy platform is designed to leverage HSV’s capacity to deliver large genes, which according to LEO makes it well suited for addressing rare, genetically driven dermatological conditions. The genetically modified HSV therapy is formulated as a topical gel that targets the deficient gene when applied directly to the skin.

“Replay’s HSV gene therapy platform holds significant promise for patients with rare genetic skin diseases, and realizing its full potential requires focused expertise in medical dermatology—an area where LEO Pharma brings decades of leadership, scale and proven execution,” LEO Pharma CEO Christophe Bourdon said. “The acquisition aligns with our strategy of investing in the most impactful opportunities in dermatology and positions LEO Pharma at the forefront of next‑generation gene therapy.” 7

LEO Pharma agreed to acquire Replay after identifying Replay as a high‑potential opportunity using its artificial intelligence (AI) scouting platform, Innoviewer™. Replay’s lead pipeline drug program is a preclinical phase candidate designed to treat dystrophic epidermolysis bullosa (DEB).

MeiraGTx buys rights to XLRP treatment from J&J for $25M upfront

MeiraGTx Holdings has agreed to acquire from Johnson & Johnson (J&J) all interests in botaretigene sparoparvovec (bota-vec), a gene therapy being developed to treat X-linked retinitis pigmentosa (XLRP).

Under the companies’ asset purchase agreement, MeiraGTx agreed to pay J&J $25 million cash upfront, a one-time regulatory and commercial milestone payment tied to U.S. approval and U.S. sales performance of bota-vec for the treatment of XLRP, plus what MeiraGTx called a high double-digit royalty on global net sales starting in mid-2029.

The sale comes nearly a year after bota-vec failed the 95-patient, Phase III LUMEOS trial (NCT04671433)  by missing the study’s primary endpoint of demonstrating statistically significant vision-guided mobility in patients with XLRP, as measured by a Visual Mobility Assessment (VMA) or maze.

However, MeiraGTx has emphasized results showing that subjects treated with bota-vec were 2.4x more likely to respond than untreated subjects. A Low Luminance Questionnaire – Patient-Reported Outcome (LLQ PRO) showed significant benefit in mobility and dim light function, qualities tested by the VMA—thus indication, according to MeiraGTx, that the maze was not sensitive enough to capture these benefits.

The company characterized data from the LUMEOS trial’s secondary endpoints as very strong, with clinically meaningful and statistically significant improvements shown in each of three domains of vision.

MeiraGTx is the commercial manufacturer of bota-vec and had collaborated in its development with J&J from Phase I development onward. The FDA has granted Fast Track and Orphan Drug Designations to bota-vec, while the European Medicines Agency has granted Priority Medicines (PRIME), Advanced Therapy Medicinal Product (ATMP), and Orphan Drug designations to bota-vec.

“This is a unique opportunity to gain an asset at this stage in development with data supporting a meaningful benefit in patients with no alternative treatment, many of whom are waiting for this life changing therapy and hoping for expeditious approval,” said Alexandria Forbes, PhD, MeiraGTX’s president and CEO. 8

She added that MeiraGTx intends to start filing a Biologics License Agreement (BLA) with the FDA and applications for regulatory approval in the European Union and Japan as soon as possible.

 

References

1. Regeneron Pharmaceuticals. Otarmeni™ (lunsotogene parvec-cwha) Approved by FDA as First and Only Gene Therapy for Genetic Hearing Loss; Regeneron to Provide Otarmeni for Free in the U.S. April 23, 2026. (Last accessed May 1, 2026)

2. Intellia Therapeutics. Intellia Therapeutics Reports Positive Phase 3 Results in Hereditary Angioedema, Marking a Global First for In Vivo Gene Editing. April 27, 2026. (Last accessed May 1, 2026).

3. Genetic Engineering & Biotechnology News. Genomics Pioneer and Life Sciences Entrepreneur J. Craig Venter Dies at 79. April 30, 2026. (Last accessed May 1, 2026)

4. Craig Venter Institute. J. Craig Venter, genomics pioneer and founder of JCVI and Diploid Genomics, Inc., dies at 79. April 29, 2026. (Last accessed May 1, 2026)

5. Rocket Pharmaceuticals. Rocket Pharmaceuticals Announces $180 Million Sale of Priority Review Voucher. April 28, 2026. (Last accessed May 3, 2026)

6. Passage Bio. Form 8-K, filed April 28, 2026. (Last accessed May 5,2026)

7. LEO Pharma. LEO Pharma bolsters rare skin disease focus through acquisition of Replay gene therapy platform. April 30, 2026. (Last accessed May 3, 2026)

8. MeiraGTx Holdings. MeiraGTx Announces the Acquisition of Botaretigene Sparoparvovec (bota-vec) for the Treatment of X-linked Retinitis Pigmentosa (XLRP). April 16, 2026. (Last accessed May 3, 2026)

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Next Gen Leadership Awards Presented at the AGBT Agricultural Meeting

Last month, the AGBT Agricultural Meeting was held in Phoenix, Arizona. The conference is focused on agricultural genomics—plant and animal genetics. During the meeting, the recipients of the 2026 Next Gen Leadership Awards were announced.

These awards recognize outstanding early-career scientists and graduate students whose work and potential are shaping the future of agricultural genomics, including advances in plant and animal genomics. Award recipients receive financial support to attend and present their research at the AGBT Agricultural Meeting, with opportunities to engage with leaders in the field and build connections across the genomics community.

“These awardees reflect the strength and diversity of emerging talent in agricultural genomics,” said Sarah Hearne, PhD, chief science and innovation officer at CIMMYT and co-chair of the AGBT Agriculture Scientific Organizing Committee. “AGBT Agriculture plays an important role in bringing these scientists into conversation with leaders across the field, helping accelerate the translation of genomics into practice.”

The awardees represent rising leaders in agricultural genomics, advancing research across genomic variability, genetic analysis, molecular diagnostics, pathogen surveillance, and quantitative trait genomics to improve crop performance, strengthen food safety, and advance sustainable agriculture.

“This award represents a transformative opportunity to grow as a scientist and contribute more effectively to innovation in animal breeding,” said Larissa Bordin Temp, a 2026 Next Gen Leadership Award recipient.

The 2026 AGBT Agricultural Meeting Next Gen Leadership awardees were:

  • Boris ME Alladassi, PhD: postdoctoral research associate at the University of Illinois Urbana-Champaign
    • Research focus: Connecting the evolutionary and statistical views of epistasis in quantitative trait genomics
  • Mythri Bikkasani: graduate student at Punjab Agricultural University, India
    • Research focus: Connecting the dots: from high-throughput feed phenotyping to genomic dissection of heterosis in maize
  • Larissa Bordin Temp: graduate student at São Paulo State University, Faculty of Agricultural and Veterinary Sciences
    • Research focus: Genomic evaluation of rump fat–adjusted residual feed intake in zebu cattle: implications for selection strategies
  • Lauren Johnson: graduate student at Gluck Equine Research Center, University of Kentucky
    • Research focus: Functional introgression within the horse mhc genes
  • Mehak Kapoor: graduate assistant at Iowa State University
    • Research focus: Cell-type resolved gene expression signatures to identify and predict persistent PRRSV infection
  • Pedro Nuñez Romano, PhD: postdoctoral researcher at Universitat Politècnica de València
    • Research focus: Integrating technology to refine the estimation of social genetic effects in pigs
  • Viona Osei: graduate student at Tuskegee University
    • Research focus: Exploiting genomic variability in Listeria for the development of molecular diagnostic markers
  • Kyungyong Seong, PhD: postdoctoral fellow at the University of California, Davis
    • Research focus: Resurrection of the plant immune receptor Sr50 to overcome pathogen immune evasion
  • Jade van Wijk: graduate student at Earlham Institute
    • Research focus: Using airborne DNA sequencing to monitor sporulation, infection and relative abundance of cereal rust fungi

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Matthew Rabinowitz: Engineering a New Era of Diagnosis

Jonathan D. Grinstein, PhD, North American Editor of Inside Precision Medicine, hosts a new series called Behind the Breakthroughs that features the people shaping the future of medicine. With each episode, Jonathan gives listeners access to his guests’ motivational tales and visions for this emerging, game-changing field.

Matthew Rabinowitz switched from engineering and computational research to medicine after a breakthrough on the Human Genome Project. He realized that telecommunications, aerospace, and machine learning technologies could help him understand human biology. His shift in focus was influenced not only by scientific interest but also by personal loss, including the deaths of family members affected by genetic conditions. These experiences convinced him that current diagnostic methods were inadequate, especially for patients and families in critical situations.

After founding Natera, Rabinowitz and his team developed Panorama Prenatal Test, a noninvasive prenatal test. This technology uses DNA variant analysis, Bayesian statistical methods, and machine learning to detect genetic conditions in cell-free fetal DNA in maternal blood samples. It increased accuracy, accessibility, and reduced invasive procedures. Myome, his new project, uses whole genome sequencing to find rare diseases. Myome uses AI models to assess cancer and cardiovascular disease risks using genomic and clinical data to improve early detection and prevention.

In this episode, Rabinowitz discusses regulatory constraints, fragmented data systems, and difficulties translating complex genetic information into clinical decisions. In the long run, he wants to create blood test diagnostics that can predict health and allow proactive medical intervention.

Rabinowitz uses several technical engineering and computational concepts, including:

  • Packet Switching: a method of dividing data into smaller units that are transmitted independently and reassembled at their destination
  • Transformer Model: a type of artificial intelligence system that processes entire datasets simultaneously to identify relationships between elements, widely used in modern AI systems such as GPT
  • Gradient Descent: an iterative method used in machine learning to minimize error by adjusting model parameters

This interview has been edited for length and clarity.

 

IPM: What originally drew you into applying engineering and machine learning to genetics and clinical diagnostics?

Rabinowitz: There was all this incredible work happening in the early 2000s around the Human Genome Project, along with applications of signal processing and machine learning, which is what I focused on during my electrical engineering training.

There were really three catalysts for me.

One was in 2003, when my sister gave birth to a child with Down syndrome at one of the top hospitals in the country, and they didn’t know until he was born. I spent six days flying around trying to help. They went through one procedure after another and after six days, the baby died from complications. It was absolutely horrific.

Second, I couldn’t believe that we had all these advanced technologies in our phones, laptops, and spacecraft, but they hadn’t made their way into clinical diagnostics. At that point, I felt I had to apply my background in signal processing and early machine learning to these problems.

The third reason was about 15 years ago, I lost a child due to a genetic condition, an absolutely devastating experience. After going through that, I felt there was a path I needed to follow.

The engineer in me took over. It felt like a problem I had to solve. It was like being struck twice: unrelated events, but the same kind of tragedy.

That’s when we used a pregnancy sample to apply for NIH funding to improve prenatal testing. We got that grant, then several others, and ultimately built Panorama, which has transformed pregnancy care globally.

From there, one thing led to another. Now, through Myome and companies like Natera, we’re working on projects that could save the U.S. healthcare system around $200 billion per year. It’s been a very personal mission. 

 

IPM: What are you seeing today with whole genome analysis that feels fundamentally new or different?

Rabinowitz: We’re now diagnosing conditions with whole genome analysis that simply weren’t detectable before. Myome has largely led the charge.

When I look at these case studies today, I get the same feeling I had 20 years ago. How were we not able to see this before?

We’ve spent a lot of time extracting signal from noise so you don’t need multiple sequential tests. You can start with the whole genome and layer analyses. This includes SNPs, CNVs, difficult deletions, tandem repeats, mitochondrial DNA, and methylation.

One example: an eight-year-old with developmental delay, autism, and hypotonia had already undergone exome sequencing with no findings. We identified a subtle deletion about one kilobase involving a single exon too large for short-read breakpoints and too small for coverage changes. That finding completely changed the child’s life.

Another example: a man in his mid-20s with dystonia, convulsions, and vomiting had undergone standard neuromuscular panels. They missed a tandem repeat very difficult to detect with short-read or exome sequencing. We developed new statistical methods and identified the breakpoints, which changed his life.

More broadly, rare disease costs in the U.S. are about $1 trillion annually with ~47 physicians involved over a 4–7 year diagnostic journey and massive lost productivity. The fact that we can now catch these cases is remarkable.

On the pregnancy side the belief was that the issue was solvable, but the technologies were limited. People at the time used shotgun sequencing and looked at DNA quantity. We instead analyzed SNPs between individuals.

We built a massively multiplexed PCR system ~20,000 primers in a single reaction. The challenge is noise, cross reactions, and primer dimers. We developed a machine learning optimization so every primer is tuned relative to every other, standardizing thermodynamics across the system.

From there, we built a statistical framework integrating across trillions of hypotheses, crossover events, noise, and fetal fraction. When it converges, you see a clear maximum likelihood peak that tells you what’s happening. If not, you know something is wrong.

This allowed us to detect things others couldn’t: very high sensitivity for aneuploidy and structural variants like microdeletions.

We could detect triploidy and vanishing twins, determine zygosity, and even de novo mutations, which are more than five times as common as Down syndrome. It was a completely new approach combining passion, engineering, and statistics.

 

IPM: Why can’t we have one universal test that does everything?

Rabinowitz: The short answer is that there’s so much more we can extract from each sample, especially with AI.

These transformer models trained to predict the next word require learning enormous context. With gradient descent, backpropagation, and large datasets, the performance is extraordinary. We didn’t fully appreciate the significance early on but today the possibilities are enormous.

That said, you can’t have one universal test. First, sample context matters. In pregnancy, you’re analyzing fetal cell-free DNA very different from adult disease testing. Second, it’s not just blood. There are many analytes. Beyond DNA, you need methylation, RNA, proteins. Most diseases require a multi-analyte approach. Third, regulation. You need to validate each test rigorously. You can’t validate everything at once across the genome. We also have variants of unknown significance. If you look for everything, interpretation becomes a problem.

So you have to focus your inquiry and ensure results are validated and actionable. That said, from a single blood draw, we can already do an incredible amount.

 

IPM: How has cfDNA and noninvasive testing evolved with AI?

Rabinowitz: Around 2017–2018, Natera began applying deep learning to diagnostics. [It was] one of the first large-scale uses in genetic testing. We had used neural networks earlier (e.g., in HIV mutation analysis) but this was different.

We applied convolutional neural networks to detect microdeletions in low fractions of cell-free DNA. A key example is 22q11.2 deletion syndrome. This occurs in about one in every 1,500 to 2,000 pregnancies. It’s more common than many screened conditions. Early detection allows intervention at birth. We initially used classical statistics, but after generating millions of samples, we trained deep learning models. The AI learned noise patterns and edge cases better than we could model, like Kasparov versus Deep Blue.

In a study of ~20,000 patients, we saw 100% sensitivity for larger deletions and ~83% for smaller ones, with a specificity of 99.95%. That translated to a positive predictive value (PPV) of ~53%, compared to 3–5% clinicians are used to.

Despite this, adoption has been slow due to reimbursement and guidelines, which is frustrating, because many children still miss early diagnosis.

 

IPM: Looking forward, how is AI transforming broader healthcare and genomics?

Rabinowitz: Today, we’re combining whole genome sequencing with AI and clinical data to predict disease risk far more accurately than even five years ago.

Across ~30 major diseases we can now predict susceptibility at a transformative level. If applied broadly, for example to people over 45, we could save over $200 billion annually by catching diseases earlier. Many interventions are simple like diet and lifestyle. Even small improvements matter. Every 1% increase in sensitivity can mean ~$7 billion in savings.

We’re also predicting neoantigens for personalized cancer vaccines, training on real patient outcomes—something that wasn’t possible before. And we’re building foundational genomic models, like language models, that learn the structure of the genome itself.

So across diagnostics, treatment, and prevention, AI is fundamentally transforming the field.

 

IPM: You mentioned earlier that you underestimated neural networks. What changed your perspective?

Rabinowitz: Around 2005, we were applying machine learning to genetics. We weren’t wrong, but we underestimated neural networks. We worked on HIV drug resistance. predicting which mutations respond to which therapies.

We used lasso regression, support vector machines, [and] carefully constrained models. Neural networks didn’t perform as well, which is what we expected. Our mindset was to control complexity to avoid overfitting. What we didn’t anticipate was massive data, stochastic training, and compute power, which allowed neural networks to escape local minima and scale. 

In 2010, I had a patent on training neural networks with memory. It lapsed because Stanford didn’t maintain it. That was right before Google Brain scaled these approaches. The lesson is to stay open-minded. Technology can open possibilities you don’t see coming.

 

IPM: How do you see the future of diagnostics evolving from a single blood draw?

Rabinowitz: We’re moving toward a world where a single blood draw can tell us an enormous amount. Historically, progress was slow: blood cell counting in the 1800s, automation in the mid-1900s, cell-free DNA in the 1990s. Since then, progress has been explosive. From one sample, we can identify incidental findings (e.g., rare diseases, pharmacogenomics, and predictive risk) across many conditions. We can also detect cancer noninvasively through circulating DNA.

The capabilities are remarkable, but the genome is complex—three billion bases, with interactions that require enormous data to model.

 

IPM: What challenges remain in making these technologies widely usable?

Rabinowitz: Two main challenges. First, data, standardizing and aggregating clinical data across institutions, is historically very fragmented. AI is helping, but more coordination is needed.

Second, education. As we generate more information, explaining it to doctors and patients becomes harder. What’s known, what’s uncertain, and what action to take. At Myome and Natera, we invest heavily in genetic counseling. But across the field, there’s a tendency to simplify by withholding information. That won’t scale. We need better ways to communicate complexity responsibly.

 

IPM: How important is diversity and multi-ethnic data in building accurate models?

Rabinowitz: It’s absolutely critical and still underserved. Many models were trained on homogeneous populations, limiting accuracy. We’ve focused on building multi-ethnic models using diverse datasets and functional genomics, but we still need more data from underrepresented populations.

For example, in cardiovascular disease, we built a multi-ethnic model using large datasets.

We were able to reclassify ~50% of patients in the intermediate-risk category, identifying who is truly high risk (>20%) versus low risk (<5%). That improved decision-making significantly with over 10% improvement in classification. When followed over time, outcomes matched predictions closely.

This has huge implications for individuals and for healthcare systems. By identifying risk earlier and intervening, often with simple lifestyle changes, we can reduce costs and improve outcomes at scale. That’s why building diverse, high-quality datasets is so important. It’s one of the most powerful ways to improve healthcare globally.

 

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Chromosome Engineering Reveals New Locus for Fusarium Resistance in Wheat

Fusarium head blight (FHB) remains one of the most destructive diseases in global wheat production, and its impact is only intensifying. Warmer climates and crop rotations that favor pathogen survival have expanded the prevalence of FHB outbreaks, leading to major yield losses and contamination of grain with mycotoxins such as deoxynivalenol (DON), nivalenol (NIV), and zearalenone (ZEN).

While fungicides offer partial control, reduced sensitivity and rising costs have made genetic resistance in wheat the most sustainable long‑term strategy. Yet despite decades of breeding, only a handful of major FHB resistance loci—Fhb1 through Fhb9—have been formally designated, and just two have been cloned. The scarcity of strong, deployable resistance genes has become a bottleneck for wheat improvement.

A new study published in the Journal of Experimental Botany, “Identification of a novel Fusarium head blight resistance locus Fhb.Er‑1StL from Elymus repens introgressed into wheat,” expands that genetic toolkit. Researchers at Sichuan Agricultural University report the discovery of a previously unknown FHB resistance locus, Fhb.Er‑1StL, derived from the wild grass Elymus repens—a species better known as an agricultural weed than a genomic resource.

“Both research and breeding practice have shown that developing and deploying resistant wheat cultivars is the fundamental solution to FHB,” said first author Fei Wang. “However, current efforts are limited by a scarcity of major resistance sources, narrow genetic backgrounds, and inefficient use of resistance genes.”

The team began by characterizing the genome of a wheat E. repens partial amphidiploid, P1142‑1‑2, which carries the full wheat genome plus seven pairs of alien chromosomes or chromosome fragments. Using sequential GISH and FISH cytogenetics, they mapped the alien chromatin and identified a pair of chromosomes containing the long arm of the E. repens 1St chromosome. From crosses with the susceptible wheat cultivar Chuannong16, they isolated two derivative lines carrying either a 1StL isochromosome or a 1StL telosome, both of which conferred strong resistance to FHB.

To pinpoint the resistance locus, the researchers applied a targeted sequencing approach using the Wheat–St 45K liquid microarray GBTS platform. This allowed the researchers to precisely identify the alien 1StL segment and develop markers to track it in breeding lines. Plants carrying this segment showed markedly improved resistance, and molecular assays confirmed that the region represents a previously unknown FHB resistance locus, now designated Fhb.Er‑1StL.

“We believe this work is of practical importance for accelerating the breeding of resistant, high‑yielding wheat varieties and breaking the bottleneck in FHB resistance breeding,” said senior author Yinghui Li, PhD.

Next steps include fine‑mapping the locus and generating smaller translocation lines to reduce linkage drag—an essential step before the trait can be widely deployed in commercial breeding.

“With the aid of modern genomic technologies and precise breeding strategies, Fhb.Er-1StL holds promise as a cornerstone for developing next-generation wheat cultivars with durable resistance to FHB,” concluded the authors.

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Blood Stem Cells Evade Immune Attack in Aplastic Anemia Through Gene Mutations

Scientists headed by a team at St. Jude Children’s Research Hospital have found that in individuals with the life-threatening blood disorder aplastic anemia (AA), different blood stem cells within the same person independently acquire gene mutations that allow cells to escape the immune attack. Through their study, the team, together with collaborating institutions, used state-of-the-art genomic techniques to profile 619 children and adults with AA. The study showed that for some patients, these “rescuing” stem cell clones were enough to restore blood production and provide long-term remission.

“We found that each patient with aplastic anemia that escapes autoimmunity has multiple, independent genetic events in different blood stem cells that allow those cells to escape autoimmunity,” said Marcin Wlodarski, MD, PhD, St. Jude Department of Hematology. “Stem cells silence the risk HLA allele through several mechanisms, and our data show that these events are protective, benign events that don’t cause progression to MDS or leukemia, even when the rescued clones grow and dominate the bone marrow.”

Corresponding author Wlodarski and colleagues reported on the study, which they say includes the largest pediatric cohort of its kind reported to date, in Nature Genetics. In their paper titled “High-resolution single-cell mapping of clonal hematopoiesis and structural variation in aplastic anemia,” the team wrote, “These findings reveal parallel evolutionary pathways used by hematopoietic cells to evade immune attack.”

Aplastic anemia is a rare, life-threatening bone marrow failure (BMF) syndrome where patients are unable to make enough blood cells due to the immune system’s attack on hematopoietic stem and progenitor cells (HSPCs). The condition can progress to myelodysplastic syndrome (MDS) and leukemia.

In AA, autoreactive T cells target and destroy blood stem cells that display peptides on a specific protein on their surface. These are encoded by the human leukocyte antigen (HLA) gene. Each person inherits one copy of this gene from each parent, which can have different variations. People with aplastic anemia often carry a particular “risk” HLA allele (gene variant) that is thought to trigger the disease. As the authors noted, “While the precise mechanism underlying HSPC recognition by autoimmune T cells remains elusive, specific human leukocyte antigen (HLA) alleles are overrepresented in patients with AA compared with healthy controls, suggesting a role in aberrant immune recognition.”

Some blood stem cells evade the immune attack by acquiring changes that silence the risk HLA allele. This can happen via loss-of-function HLA mutations or through uniparental isodisomy 6p (UPD6p), where the risk allele is replaced with a non-risk allele. “HLA loss, manifesting as uniparental disomy of chromosome 6p (UPD6p) or loss-of-function (LOF) mutations in HLA, is postulated to inactivate HLA risk alleles (presumed to mediate autoantigen presentation), effectively shielding HSPCs from autoimmune attack,” the investigators noted. Two other types of escape in blood stem cells are known: paroxysmal nocturnal hemoglobinuria (PNH) or mutations in clonal hematopoiesis (CHIP) genes. However, it was unclear if all these changes arise in a single stem cell or arise independently to help the blood stem cells hide from the immune system. It was also unclear how this process of immune evasion impacted clinical outcomes and cancer risk.

“The clinical implications of clonal alterations in AA vary,” the investigators stated. “HLA loss is generally considered a nonmalignant adaptive lesion, large PNH clones require complement inhibitor therapy, and CHIP-mutant clones may be associated with MDS, thereby necessitating hematopoietic stem cell transplantation (HSCT).”

(L to R) Corresponding author Marcin Wlodarski, MD, PhD, and lab member Diantha Van De Vlekkert, MSc, both of the St. Jude Department of Hematology, and second author Sushree Sahoo, PhD, formerly of the St. Jude Department of Hematology. [St. Jude Children's Research Hospital]
(L to R) Corresponding author Marcin Wlodarski, MD, PhD, and lab member Diantha Van De Vlekkert, both of the St. Jude Department of Hematology, and second author Sushree Sahoo, PhD, formerly of the St. Jude Department of Hematology. [St. Jude Children’s Research Hospital]

Blood stem cells give rise to all other blood cells, meaning their progeny are genetically identical, including any mutations gained over time. The relative abundance of a specific stem cell’s genetic “clones” measures the genetic diversity of these blood-making cells. Using single-cell analyses, the researchers showed that protective mutations happen independently in different blood stem cells and not sequentially within a single cell. These independent clones then repopulate the marrow without being found and killed by the immune system. “We saw that patients with blood stem cell clones that escape autoimmunity can improve their blood counts,” Wlodarski said. “We also learned that these clones do not indicate an increased risk for leukemia. On the contrary, they often indicate the possibility of long-lasting remission.”

To assess these clones, the scientists analyzed bone marrow and blood samples from 619 (256 children and 363 adults) patients with AA. “We present a high-resolution genomic landscape in AA patients using single-cell targeted DNA/protein sequencing, PacBio long-read whole-genome sequencing (WGS), and single-cell WGS,” they explained. They found that overall, 69% of patients carried at least one acquired change: HLA mutations or UPD6p clones were found in 16%, PNH clones in 44%, and CHIP mutations in 21%.

First author Masanori Yoshida, MD, PhD, St. Jude Department of Hematology, then established and applied a single-cell DNA sequencing assay to simultaneously profile mutations and cell-surface proteins of 304,902 single cells from 48 samples. The study was complemented by long-read whole-genome sequencing and single-cell whole-genome sequencing.

The experiments showed that acquired mutations are just as common in children as in adults, but in pediatric patients, 65% of the CHIP mutations occurred in just three genes (BCOR, BCORL1, and ASXL1), compared with 27% in adults. Because age-related CHIP mutations are not expected to preexist in children, these mutations seem to be immune-escape events acquired in response to the autoimmune attack. “In children, where preexisting CHIP is not expected, mutations in these three genes may represent bona fide immune escape mechanisms arising in direct response to T-cell-mediated attack,” the authors stated.

To understand how these protective events arise and to count them precisely, the authors performed whole-genome sequencing on many single blood stem cells. They expected to see one to three events per individual; instead, they found a median of three per patient, and in one patient, 15 independent clones, all resulting in the loss of the risk HLA allele, showing convergent evolution to escape a strong immune attack. “Strikingly, HLA loss clones emerge independently through mutational events that converge on inactivating a single specific HLA risk allele, with up to 15 clones per patient identified using the scWGS platform … Our analyses reveal that somatic alterations in AA arise as independent clones rather than through sequential acquisition, and most patients carry multiple independent clones,” the investigators noted.

That extreme diversity pointed to an unusual, convergent evolutionary process, so the scientists reconstructed a phylogenetic “family tree” of individual blood stem cells by reading all mutations acquired throughout life in single whole genomes. This method enabled them to pinpoint each clone’s origin. “We had expected that these mutations occur right before disease onset,” Wlodarski said. “But we found some of these HLA-loss clones arose many years before clinical diagnosis.”

The team also showed that long-lived, rescued clones had higher expression of CD34, a surface marker for blood stem and progenitor cells. This suggests that CD34 enrichment could serve as a biomarker of long-lasting recovery. In addition, clones with loss of HLA risk alleles and CHIP mutations almost never co-occurred in the same cells, indicating that HLA loss provides enough of a proliferative advantage on its own that additional CHIP mutations, which can predispose to MDS, are not selected. So, they appear to act as protective events against their MDS and leukemia evolution.

“Clones with higher CD34+ expression levels measured in our scDNAseq/protein analysis, particularly those with HLA-loss alterations, demonstrated long-term fitness, multilineage contribution, and were often associated with stable blood counts and prolonged treatment-free intervals,” the team pointed out. These results challenge prior assumptions about when and how protective clones arise in aplastic anemia, and their presence can be a factor in restoring blood formation.

“Aplastic anemia shows us convergent evolution in miniature: Multiple independent mutational events arise in different cells, all leading to the same escape from autoimmunity,” Wlodarski said. “It shows the amazing nature of human hematopoiesis to cure itself from bad actors, like the autoimmune T cells, and reconstitute the bone marrow.” In their paper, the team concluded, “These findings enhance our understanding of clonal dynamics in AA and provide a foundation for future precision medicine approaches to address BMF in this life-threatening syndrome.”

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TRACS Enables Strain-Level Tracking of Microbial Transmission

Tracking microbes is challenging, particularly when there are coexisting strains of the same species within metagenomic data. However, overcoming that challenge is important for inferring transmission of both pathogenic and commensal microbes.

A new tool, called TRAnsmision Clustering of Strains (TRACS), distinguishes between closely related bacterial strains. The “highly accurate algorithm” can be used for “estimating genetic distances between strains at the level of individual single nucleotide polymorphisms, which is robust to intra-species diversity within the host.”

Researchers used the TRACS tool to map the transmission of SARS-CoV-2, Streptococcus pneumoniae, and Plasmodium falciparum (the causative agent of malaria) across different populations. The tool may play an important role in infection prevention, outbreak response, and the development of treatments designed to help the human microbiome fight infection. They note that this tool can be used across microbial kingdoms to uncover strain dynamics.

“Traditionally, this has been very difficult for us to achieve, yet it is incredibly important to know, as people can carry several slightly different versions or strains of the same species at once, which makes it challenging to understand how microbes move between individuals,” notes Gerry Tonkin-Hill, PhD, group leader at the the Peter MacCallum Cancer Centre and the Peter Doherty Institute at the University of Melbourne, Australia. “Using this new technology, we can now overcome this challenge and gain a clearer picture of how microbes are shared between people. This will give us a better understanding of how microbes spread to help us prevent infection in vulnerable populations, like our cancer patients.”

This work is published in Nature Microbiology in the paper, “Strain-level transmission inference across multi-kingdom metagenomic data using TRACS.”

Being able to track the spread of pathogens using genomics has become a major tool in public health and can help inform new ways to prevent transmission. Additionally, it can help understand more about how lifestyle and environmental factors are involved in the transmission of these pathogens, and their role in the microbiome.

Currently, genomic tools used to track multiple bacterial species do not have the speed and flexibility required for routine public health monitoring and can struggle to distinguish between samples transmitted recently and those transmitted years ago. Furthermore, it can be difficult to continuously add in new samples, making real-time surveillance difficult.

The TRACS algorithm identifies and analyzes Single Nucleotide Polymorphisms (SNPs) to estimate how closely related the pathogens are, and if they are likely to have recently been transmitted. This approach allows for the continuous integration of new samples, making it an ideal tool for accurately identifying transmission networks and ruling out transmission events in ongoing public health applications.

In this new study, the team used TRACS to map pathogen transmission networks across three different populations, all of which had different genomic data. They applied it to SARS-CoV-2 data from U.K. hospitals, deep population sequencing data of Streptococcus pneumoniae and single-cell genome sequencing data from malaria patients infected with Plasmodium falciparum. They found that the tool was able to identify different pathogens in one sample and infer where these were each transmitted.

They also used TRACS to study how microbes are passed from mothers to infants and found that one beneficial bacterium, Bifidobacterium breve, persisted in infants longer than previously recognized, something that previous methods have missed.

More superficially, the authors note that “applying TRACS to gut metagenomic samples from a mother–infant cohort revealed species-specific transmission rates and identified increased the persistence of Bifidobacterium breve in infants, a finding previously missed owing to the presence of multiple strains.”

“This research could support the development of new treatments that use beneficial microbes to improve health,” notes Trevor Lawley, PhD, group leader at the Wellcome Sanger Institute. “By understanding exactly how microbes move between people and which of them are more likely to thrive in their microbiome, we could design better ways to increase helpful gut microbes and investigate whether there are ways to use these to help prevent infections, opening the door to safer healthcare environments and new microbiome-based therapies.”

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Machine Learning Tool Helps Improve Type 1 Diabetes Prediction

A machine learning model can improve genetic prediction of type 1 diabetes by as much as 10%, show results from a University of California, San Diego study.

The researchers used the machine‑learning model T1GRS to improve on a gold standard polygenic genetic risk score used to predict who is likely to develop the condition called GRS2.

Type 1 diabetes is an autoimmune condition that impacts around 2 million people in the U.S. While it is a multifactorial condition, genetics plays a big role and around 50% of a person’s susceptibility comes from genetics.

“The natural history of type 1 diabetes suggests that the disease occurs in genetically susceptible individuals exposed to environmental triggers, leading to the development of islet-specific autoantibodies and autoreactive T cells and progressive loss of insulin secretory function, although the underlying etiology is not fully understood,” write lead author Kyle Gaulton, PhD, associate professor of pediatrics at UC San Diego School of Medicine, and colleagues in Nature Genetics.

The GRS2 polygenic risk score has been widely tested and can be used to predict newborns who are at high risk of developing type 1 diabetes. While early prediction can’t necessarily stop the disease it can help to prevent emergencies like diabetic ketoacidosis at diagnosis, allow families time to prepare and could allow use of therapies to delay onset of the condition.

In this study, Gaulton and colleagues carried out a genome‑wide association study in 20,355 people with type 1 diabetes and 797,363 non‑diabetic Europeans, as well as a further analysis around the MHC region in 10,107 diabetic and 19,639 nondiabetic individuals.

“The MHC has ‘blocks’ of co-inherited genetic information that are very highly enriched in individuals with type 1 diabetes,” said co-first author Emily Griffin, PhD, a postdoctoral fellow in Gaulton’s lab. “If you have them, it doesn’t mean that you’re going to get diabetes, but if you don’t have them, it means you have a very low chance of getting diabetes.”

Overall 160 risk signals were identified, and the team trained their T1GRS model to predict who was likely to develop type 1 diabetes based on their genetics. The model was able to improve on the GRS2 model predictions by up to 10% in both populations of European and African American ancestry.

Overall the new score correctly flagged about 89 of 100 people with type 1 diabetes while correctly reassuring about 84 of 100 people without the disease.

“Our results highlight the value of combining the results of genetic association studies with machine learning methods to improve the prediction of complex diseases,” conclude the authors.

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Genomics Pioneer and Life Sciences Entrepreneur J. Craig Venter Dies at 79

J. Craig Venter, PhD, the founder, board chair, and CEO of the J. Craig Venter Institute (JCVI) has died in San Diego following a brief hospitalization for unexpected side effects that arose from the treatment of a recently diagnosed cancer, noted the JCVI in a press statement.

Venter helped define modern genomics and launch the field of synthetic biology. He was skillful in building interdisciplinary teams, pushing for new ideas and faster methods, and insisting that discovery should translate into real-world impact. He was also a major advocate for strong federal science funding and for partnerships that accelerate progress across government, academia, and industry.

“Craig believed that science moves forward when people are willing to think differently, move decisively, and build what doesn’t yet exist,” said Anders Dale, PhD, president of JCVI. “His leadership and vision reshaped genomics and helped ignite synthetic biology. We will honor his legacy by continuing the mission he built—advancing genomic science, championing the public investments that make discovery possible, and partnering broadly to turn knowledge into impact.”

“Venter has been recognized as an essential force in the impetus to evolve genomics from a slow, academic discipline into a fast-moving, data-driven, and commercially relevant enterprise, leaving a lasting imprint on biotechnology, medicine, and synthetic biology,” says John Sterling, GEN’s Editor in Chief, who has known and worked editorially with Venter over the past 35 years.

“Venter was controversial and often challenged the scientific orthodoxy, with critics accusing him of hype and going overboard on privatization. To many, he was a visionary focusing on technological acceleration and blending academic science with the zeal of an entrepreneur. Supporters saw him as a pioneer who sped up genomics by years.”

At the NIH, he played a key role in driving gene discovery using expressed sequence tags (ESTs), enabling rapid identification of large numbers of human genes and accelerating genome mapping efforts. He went on to lead efforts that, along with the NIH, produced the first draft sequences of the human genome, a milestone that helped usher biology into the digital age. He and colleagues later published the first high-quality diploid human genome, demonstrating the importance of capturing genetic variation inherited from both parents.

In synthetic biology, Venter and his teams constructed the first self-replicating bacterial cell controlled by a chemically synthesized genome—proof that genomes could be designed digitally, built from chemical components, and “booted up” to run a living cell. He also pursued scientific discovery at global scale.

Through the Sorcerer II Global Ocean Sampling Expedition, Venter and his teams used metagenomics to reveal amazing microbial diversity, reporting the discovery of millions of new genes and expanding the known universe of protein families—work that deepened understanding of the ocean microbiome and its impact on planetary systems.

Beyond his scientific achievements, and in addition to founding the JCVI, he also co-founded Synthetic Genomics, Human Longevity, and most recently Diploid Genomics, advancing efforts to translate genomics and synthetic biology into tools for the benefits of human health and environmental sustainability.

 

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New PRS Tool Identifies Inherited Risk for Eight Cardiovascular Conditions

Researchers at the Mass General Brigham Heart and Vascular Institute and collaborators have developed and validated a new integrated polygenic risk score (PRS) that estimates inherited risk across eight cardiovascular conditions using a single genetic test. The tool is a combination of a handful of genetic risk models collected into a comprehensive risk tool and is designed to improve identification of individuals at elevated risk for coronary artery disease (CAD), atrial fibrillation, type 2 diabetes, venous thromboembolism, thoracic aortic aneurysm, extreme hypertension, severe hypercholesterolemia, and elevated lipoprotein(a).

The validation study, published in the Journal of the American College of Cardiology, showed that individuals with high genetic risk scores had significantly higher odds of developing disease compared with those at average risk, including a 3.7-fold higher odds for CAD and a 4.1-fold higher odds for severe hypercholesterolemia.

“Interpreting DNA risk is new for the public as well as clinicians,” said co-senior author Pradeep Natarajan, MD, director of preventive cardiology at Mass General Brigham Heart and Vascular Institute. “It was very important to us to provide a clear genetic risk report that would be accessible and patient-friendly.”

The researchers developed the integrated PRS tool using PRSmix, an elastic-net approach that combines previously published polygenic risk scores from the Polygenic Score Catalog. The model was trained using genotype and clinical data from 245,394 participants in the NIH All of Us Research Program and validated using data from 53,306 people from the Mass General Brigham Biobank. In the validation cohort, the integrated scores demonstrated strong discrimination across all eight conditions, with individuals in the top 10% of genetic risk showing increased odds of disease, including CAD (odds ratio 3.7), type 2 diabetes (3.1), atrial fibrillation (3.0), venous thromboembolism (1.9), hypertension (2.1), and lipoprotein(a) (41.0).

Current cardiovascular risk assessments typically rely on age, sex, blood pressure, cholesterol, and other clinical factors. The Mass General team noted that these methods may miss individuals with substantial inherited risk who do not yet show clinical symptoms. By comparison, the new PRS tool gives a single genetic assessment that can be applied early in life and across multiple disease pathways simultaneously.

“Although PRS have typically been evaluated one condition at a time, a single genotyping assay enables calculation of PRS for any heritable trait without significant additional cost, creating an opportunity to assess inherited risk across multiple cardiovascular conditions simultaneously,” the researchers wrote noting the value of this new method.

In this study, the integrated PRS improved risk classification when incorporated into clinical prediction models, including better stratification of individuals near clinical decision thresholds for cardiovascular disease. The system also generated standardized risk categories—high, average, or low—for each condition and presented results in clinician-facing and patient-facing formats that can be integrated into electronic health records.

Clinically, the new PRS is could be use to identify people whose inherited risk could provide the opportunity for preventive interventions such as increased monitoring, lifestyle modification, or preventive therapies, even when conventional risk factors appear normal. For CAD specifically, the findings suggest that individuals with high polygenic risk may have risk levels comparable to other established high-risk groups, despite modest or normal cholesterol levels.

The researchers also evaluated how the tool could work across diverse populations and clinical settings. They found that while the PRS performed consistently across ancestry groups, predictive strength was reduced in individuals with greater genetic variation from people of European ancestry, exposing the inherent limitations in current genomic reference datasets. Despite this, the integrated framework was designed to allow updating as new data become available.

The PRS is currently available through Mass General Brigham Laboratory for Molecular Medicine and Broad Clinical Labs. The researchers said that next steps to further refine the tool include broader prospective validation across diverse populations, evaluation its cost-effectiveness, and research to determine how genetic risk information should influence clinical decision-making.

 

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