April 3, 2024Open Access

Adjusting for principal components can induce spurious associations in genome-wide association studies in admixed populations

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Authors

KGKelsey GrindeMacalester College BBBrian L. BrowningUniversity of Washington ARAlexander P. Reiner

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Implication

Observational genetic analysis reveals biased effect sizes and spurious associations in admixed populations, highlighting the need for tailored linkage disequilibrium pruning.

Key Points

Spurious associations and biased effect size estimates arise from adjusting for later principal components in admixed populations, driven primarily by collider bias.
Across all 3 cohorts, the first principal component tracks genome-wide ancestry whereas later components reflect localized linkage disequilibrium features.
Analysis of African American genomic datasets reveals that excluding high linkage disequilibrium regions fails to eliminate bias, requiring customized ld pruning.

Cite This Study

Grinde et al. (2024) studied this question.

synapsesocial.com/papers/68e708c9b6db64358768243b https://doi.org/10.1101/2024.04.02.587682

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Implication

Observational genetic analysis reveals biased effect sizes and spurious associations in admixed populations, highlighting the need for tailored linkage disequilibrium pruning.

Adjusting for principal components can induce spurious associations in genome-wide association studies in admixed populations

Discussion

Member takes

Implication

Key Points

Cite This Study

Adjusting for principal components can induce spurious associations in genome-wide association studies in admixed populations

Discussion

Member takes

Implication

Key Points

Cite This Study

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