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LANTERN method identifies ancestry-specific rare-variant associations in African American participantsNew Tool Finds Rare Genetic Clues Hidden In Mixed Heritage DNA

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Key Takeaway
Note that the LANTERN method may enhance the detection of ancestry-specific rare-variant associations in red blood cell traits.

This cohort study utilized the LANTERN (Leveraging local ANcestry Tracts to Enhance Rare variaNt aggregate associations) method to analyze red blood cell biology in African American participants from the Jackson Heart Study. The researchers compared the LANTERN approach, which utilizes local ancestry information, against an analysis that ignores local ancestry.

The study reported that a burden of rare alleles on European ancestral haplotypes in EPO was associated with both hemoglobin levels (HGB) and RBC counts. Additionally, a burden of rare alleles on African ancestral haplotypes in EPB42 was associated with HGB and RBC. Through simulation studies, the LANTERN method achieved proper control of Type 1 error while boosting power to detect associations when causal alleles predominately lie on one ancestral haplotype.

Safety and tolerability data were not reported. The study used a generalized linear mixed model framework to report associations between rare allele burdens and clinical traits. While the LANTERN method enhances rare-variant association signals compared to analyses ignoring local ancestry, the findings are based on specific ancestral haplotype associations within this cohort.

Imagine trying to solve a puzzle where some pieces come from one box and others from a completely different box. You know the final picture, but the pieces are mixed together. This is exactly how scientists have struggled to read the DNA of people with mixed ancestry for a long time.

Most genetic tests look at your whole DNA as one big mix. They assume all your genes come from the same background. But for many people in the Americas, their DNA is a blend of African, European, and Indigenous American lines. Ignoring this mix means missing important clues about health.

The Old Way Missed Big Clues

For years, researchers used standard tools to find common genetic risks. These tools worked well for common changes. They failed when looking for rare changes. Rare changes are like finding a single red marble in a bucket of blue ones. Standard tests often ignore these rare marbles because they are so uncommon.

When you mix DNA from different groups, these rare changes can hide. If a rare bad gene comes from one side of your family, a standard test might miss it. It gets lost in the noise of the mixed background. This has left many people without answers for why they get sick or why their blood counts are low.

A New Computer Switch

Scientists needed a new way to look at the puzzle. They needed a method that could separate the pieces before solving the picture. They built a new computer program called LANTERN.

Think of LANTERN as a super-powered sorter. It looks at your DNA and asks, "Which piece came from which side of your family?" It tracks the history of every small section of your genetic code. Once it knows the origin, it can check if a rare change from that specific side causes a problem.

How The Study Worked

The team tested their new tool using data from the Jackson Heart Study. This group included many African American participants. Their DNA reflects a mix of African and European ancestry. The researchers used LANTERN to look for rare changes affecting red blood cells.

They focused on two specific genes. One gene, called EPO, helps your body make red blood cells. The other, EPB42, also plays a key role in blood health. The team wanted to see if rare changes in these genes were linked to low hemoglobin or low red blood cell counts.

The results were clear and exciting. When LANTERN looked at the data, it found signals that older methods completely missed. It found that rare changes on European ancestry lines in the EPO gene were linked to lower hemoglobin levels.

It also found rare changes on African ancestry lines in the EPB42 gene were linked to both hemoglobin and red blood cell counts. These findings show that ancestry matters. The same gene can act differently depending on which side of your family it came from.

But There's A Catch

This new tool is a major step forward for science. However, it is not a new medicine you can buy at a pharmacy yet. It is a computer method for researchers. It helps scientists design better studies and find new drug targets.

This discovery helps doctors understand why some people have anemia or low blood counts. It explains that a person's background is part of the story. It tells us that one size does not fit all in genetics.

Doctors can use this knowledge to give better advice. If a patient has low blood counts, a doctor might now look at their specific ancestry. They can check for rare changes that were previously invisible. This leads to more personalized care plans.

The tool is free for other scientists to use. They can download it and test it on their own data. But more work is needed. Researchers must test it in other groups of people. They need to prove it works everywhere before it changes standard care.

Science takes time. We are building the map, but we still need to walk the path. This new tool gives us a better map. It shows us where the hidden genetic clues are hiding. Soon, we may see treatments that work specifically for people with mixed heritage. Until then, this research brings us closer to true health equity for everyone.

Study Details

Study typeCohort
EvidenceLevel 3
PublishedApr 2026
View Original Abstract ↓
Individuals with admixed ancestry comprise a significant proportion of populations of the Americas. Statistical methods have been developed to specifically leverage local ancestry inference to enhance the power and interpretability of genome-wide association studies in admixed populations. However, no such methods currently exist to test for rare-variant aggregate associations. Here we present LANTERN (Leveraging local ANcestry Tracts to Enhance Rare variaNt aggregate associations), a method that infers the alleles that lie on each ancestral haplotype and conducts rare-variant aggregate association testing in a generalized linear mixed model framework. Through simulation studies we demonstrated that LANTERN achieves proper control of Type 1 error while boosting power to detect associations when causal alleles predominately lie on one ancestral haplotype. Using data from a cohort of African American participants from the Jackson Heart Study, LANTERN identified two genes known to be involved in red-blood cell (RBC) biology when local ancestry information was incorporated. Specifically, a burden of rare alleles on European ancestral haplotypes in EPO was associated with both hemoglobin levels (HGB) and RBC counts, whereas a burden of rare alleles on African ancestral haplotypes in EPB42 was associated with HGB and RBC. In summary, LANTERN (i) allows for the identification of ancestry-specific rare-variant associations; and (ii) enhances rare-variant association signals compared to an analysis that ignores local ancestry. LANTERN is implemented in R and is freely available on GitHub.
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