Cardiovascular genetic medicine will need a different patient-finding infrastructure

Genetic medicines are changing who cardiovascular trials need to find. Eligibility is increasingly defined by a genotype or a biomarker level, and the people who meet those criteria sit inside populations of millions. Familial hypercholesterolemia affects roughly 1 in 300 people, and elevated lipoprotein(a) is even more common. The European Atherosclerosis Society estimates that about 1 in 5 people worldwide face increased cardiovascular risk from a high Lp(a) level.

Most of those people have never been tested. Sponsors have to find them before sites can screen them, and cardiovascular programs now face that problem at a scale rare disease never did.

Rare disease has already built the operating model

The challenge isn’t population size alone; trial-ready, genetically characterized patients are scarce because most people haven’t been systematically identified or tested.

Rare disease programs have spent years solving identification problems of this kind. The model has four parts:

• Direct-to-participant genetic testing, so people can find out their status without a site visit.
• Prescreening before site referral, so sites see only participants who meet the genetic and clinical criteria.
• Structured engagement between referral and randomization, and through long-term follow-up.
• Consented cohorts that can be recontacted between studies.

The results are measurable. In one Sano-supported Parkinson's program, at-home DNA testing delivered a 55% cost reduction compared with DNA testing through site visits and identified eligible patients at twice the industry benchmark. In a Sano-supported alpha-1 antitrypsin deficiency (AATD) study, 58 genetically suitable volunteers were referred, which delivered 90% of its referral target in the first four weeks of a four-month recruitment period. AATD recruitment depends on genotype confirmation, as FH trials will.

The same operating principles apply to cardiovascular disease, but at a very different scale. The methods described in precision patient finding at scale apply directly.

Where cardiovascular genetic medicine stands today

Gene editing is moving into genetically defined populations. In 2026, the New England Journal of Medicine published Phase 1b data from the Heart-2 trial of VERVE-102, an in vivo PCSK9 base editor, a year after Eli Lilly agreed to acquire Verve Therapeutics for up to $1.3 billion. Heart-2 is an open-label trial in adults with heterozygous FH or premature coronary artery disease.

Later-phase trials will need participants with a confirmed variant or a qualifying lipid profile, and genetic eligibility shows up earlier in the pipeline than most plans assume.

FH is common and mostly undiagnosed. Clinicians diagnose FH from very high LDL cholesterol, a family history of early heart disease, and physical signs such as tendon xanthomas. FH genetic testing looks for a pathogenic variant in LDLR, APOB, or PCSK9.

The bigger gap sits upstream: most people who may qualify have never been identified or tested. A 2019 Lancet Digital Health study estimated that fewer than 10% of more than 1 million people with FH in the US were identified, and a 2019 Lancet Digital Health roadmap found that most societies identify fewer than 10% of expected cases. Even diagnosed patients rarely carry a genetic result: before 2020, only about 8% of patients in the FH Foundation CASCADE FH Registry had been diagnosed through genetic testing.

Cascade screening shows what a committed system can achieve. A 2026 report on the Dutch national program describes genetic testing of 8,447 relatives between 2014 and 2024, of whom 4,312 (51.0%) were FH-positive. This is a useful planning reference: one confirmed proband can create an opportunity for cascade screening among first-degree relatives, where consent and local rules allow.

Lp(a) trials show what biomarker-defined enrollment requires at scale. Multiple Lp(a)-targeted trials are already enrolling or have enrolled large populations, but they depend on a measurement that relatively few patients have ever had. Only 0.8% of All of Us participants with health record data had an Lp(a) test, and a Cleveland Clinic analysis of 70.8 million adults found that 3.52% of people with FH had received an Lp(a) test.

Guidelines now support broader testing. However, practice has moved more slowly than guidance, which means each Lp(a) program is still having to build its own tested population, often site by site and largely from scratch.

What cardiovascular genetic trials need to do differently

For clinical operations and trial strategy leaders, the evidence points to three changes in how cardiovascular genetic trials are planned.

Feasibility begins upstream. Estimates drawn from coded diagnoses undercount FH and almost entirely miss elevated Lp(a), so site databases built on existing diagnoses capture only the small, already-identified fraction. Feasibility therefore has to ask not only how many diagnosed patients exist, but how many eligible people can realistically be found, tested and moved into a trial pathway. When testing is planned only at site activation, testing capacity sets the enrollment ceiling.

Testing becomes infrastructure. Genotype and biomarker testing need to be built into development planning early, with consent, genetic counseling and result return treated as standing infrastructure rather than trial-by-trial add-ons. When testing infrastructure is rebuilt for each trial, sponsors repeat the same identification work again and again.

Cohorts become reusable assets. One-time gene-editing therapies will need large Phase 2 and Phase 3 trials, followed by years of safety follow-up. Sponsors that build genotyped, consented populations during early development can carry them into each later phase. A participant confirmed with an LDLR variant or high Lp(a) today may qualify for several gene-editing or Lp(a)-targeted programs over the next decade, and many assets in the precision medicine pipeline for cardiometabolic conditions will run sequential trials in overlapping populations. Each new protocol can then start with a known, consented population and an established recontact pathway, reducing the risk of rebuilding the recruitment funnel from zero.

Practically, this translates into the following:

1. Define the genotype or biomarker threshold in the protocol, and build the testing step into feasibility from the start.
2. Offer at-home FH genetic testing or Lp(a) testing to interested participants, with genetic counseling for anyone who receives a result.
3. Prescreen before site referral.
4. Use each confirmed result to offer cascade screening to first-degree relatives, where consent and local rules allow it.
5. Keep participants engaged between referral and randomization, and through long-term follow-up.
6. Retain consent for recontact, so genotyped participants can be invited to later studies.

If you’re planning a cardiovascular program with genetic or biomarker-defined eligibility, get in touch.