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LANTERN: Leveraging Local Ancestry Tracts to Enhance Rare-Variant Aggregate Association Testing.

Yu Wang, Bjoernar Tuftin, Laura M Raffield et al.

42094175 PubMed ID
8 Authors
2026-04-27 Published
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Chapter I

Publication Details

Comprehensive information about this research publication

Authors

YW
Yu Wang
BT
Bjoernar Tuftin
LM
Laura M Raffield
BH
Bertha Hidalgo
SL
Sarah L Kerns
AT
Andrew T DeWan
SM
Suzanne M Leal
PL
Paul L Auer
Chapter II

Abstract

Summary of the research findings

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.

Chapter III

Analysis

Comprehensive review of ancestry and genetic findings

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Summary

Key Findings

Ancestry Insights

Traits Analysis

Historical Context

Scientific Assessment