A landmark week for cardiovascular genetics opened with huge news from the gene-editing field: Eli Lilly’s experimental therapy VERVE-102, a single-dose PCSK9 base editor designed for patients with heterozygous familial hypercholesterolemia (FH) and premature coronary artery disease (CAD), demonstrated durable cholesterol-lowering effects in early studies. While the result marks one of the strongest signs yet that in vivo gene editing could become a practical treatment for inherited cardiovascular disease, it’s just scratching the surface of the enormous number of uncharacterized genetic variants that influence cholesterol levels and heart disease risk across global populations.
The largest rare variant association with blood lipids study ever reported may provide the roadmap to heart disease mechanistic and clinical insights. In a Nature Genetics study analyzing data from more than one million individuals, researchers identified thousands of rare coding variants linked to cholesterol and triglyceride (TG) levels, including several genes strongly associated with coronary artery disease. The findings could accelerate the development of precision medicines for dyslipidemia and improve the diagnosis of inherited lipid disorders such as familial hypercholesterolemia.
Diversity and scale
FH is caused by rare mutations that raise LDL-C, increasing the risk of early-onset CAD, a leading cause of premature death worldwide. Although statins and other lipid-lowering therapies can significantly lower cardiovascular risk, FH is underdiagnosed and undertreated. Many FH-associated variants have variable penetrance, so some carriers have severe disease and others have milder symptoms, adding to the complexity.
Accurate variant-specific risk assessment is becoming increasingly important as genetic screening expands. Most genetic databases are biased toward Europeans, making it difficult to classify disease-causing variants in non-Europeans.
To fill this gap, Satoshi Koyama, MD, PhD, led a research team across academic and medical institutions in the Boston area that analyzed exome sequencing and blood lipid data (total cholesterol, LDL-C, HDL-C, and TG) from Million Veteran Program, UK Biobank, and All of Us participants. More than 230,000 participants came from historically underrepresented populations, making this one of the most diverse large-scale lipid genetics studies conducted to date.
Mechanistic and clinical implications
Their analysis uncovered nearly three million rare coding variants, including more than 214,000 predicted loss-of-function mutations, 2.7 million missense variants, and over 23,000 cryptic splice variants that may disrupt gene processing. In total, the team evaluated over 10 million variant-phenotype associations. The results revealed 800 exome-wide significant additive associations across 184 genetic loci, along with 109 recessive associations involving 53 genes. Many of the strongest signals appeared in genes already known to regulate lipid metabolism and cardiovascular disease, including PCSK9, LDLR, APOB, NPC1L1, and APOC3.
The study also identified five lipid-associated genes significantly linked to CAD risk, highlighting potential therapeutic targets. One particularly intriguing gene was RORC, which encodes the transcription factor RORγ. Previous laboratory and animal studies suggested that suppressing RORγ improves metabolic health and reduces atherosclerosis. Consistent with those findings, the study showed that loss-of-function variants in RORC appeared protective against CAD in humans.
Another key finding involved cryptic splice variants, a class of mutations often overlooked in clinical genetics. The researchers used machine-learning-based splice prediction tools to show that these variants had biological effects similar to canonical loss-of-function mutations, suggesting that many clinically important variants may be underestimated.
The study also found that 13% of missense mutations produced hypermorphic alleles that increased gene activity, unlike most loss-of-function variants. Existing computational prediction tools frequently fail to identify these variants, potentially limiting the sensitivity of current genetic testing approaches.
Koyama and colleagues also detected strong recessive genetic effects that standard additive models may miss entirely. Because homozygous rare variants are uncommon, their contribution to disease has historically been difficult to measure. The findings suggest that recessive inheritance may explain part of the “missing heritability” in complex cardiovascular disease.
The researchers found that most rare variants exerted similar effects across populations, even when variant frequencies differed substantially between ancestries. The study identified 130 alleles observed primarily or exclusively in non-European populations, emphasizing the importance of expanding genetic research beyond European cohorts to improve equitable diagnosis and drug discovery.
From screening to saving hearts
Beyond biological discovery, the study carries important clinical implications. By comparing their findings with curated pathogenic variant databases, the investigators confirmed many established classifications while identifying variants that may warrant reclassification. Two newly highlighted variants enriched in non-European populations may represent previously underrecognized causes of familial hypercholesterolemia.
Although the research focused mainly on rare coding variants rather than noncoding DNA, the authors argue that population-scale sequencing studies can now provide clinically actionable insights into disease mechanisms, pathogenicity, penetrance, and prognosis. Together, the findings offer a powerful new resource for cardiovascular genetics at a time when therapies such as PCSK9 gene editing are beginning to move from concept to clinic.
