BIGFAM - variance components analysis from relatives without genotype

Abstract Estimating variance components of phenotypes provides a fundamental basis for understanding complex traits. However, most existing methods require genotype data, which is costly to obtain and often unavailable, limiting their scalability. To address this limitation, we developed BIGFAM, a g...

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Main Authors: Jaeeun Jerry Lee, Buhm Han
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-025-60502-0
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author Jaeeun Jerry Lee
Buhm Han
author_facet Jaeeun Jerry Lee
Buhm Han
author_sort Jaeeun Jerry Lee
collection DOAJ
description Abstract Estimating variance components of phenotypes provides a fundamental basis for understanding complex traits. However, most existing methods require genotype data, which is costly to obtain and often unavailable, limiting their scalability. To address this limitation, we developed BIGFAM, a genotype-free framework that estimates variance components by genetic, shared environmental, and X chromosome effects using only phenotype data from relative pairs. We analyze variance components in Generation Scotland and UK Biobank datasets and demonstrate that BIGFAM’s estimates show high correlation with genotype-based methods ( $$r$$ r  = 0.85 for heritability and 0.64 for X chromosome components). We identify strong nuclear-family-specific shared environmental effects in dietary-related phenotypes. These results establish a new approach for analyzing variance components across diverse populations without the need for genetic data.
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spelling doaj-art-2e0db93c1448446896986fbdca68f3382025-08-20T03:45:33ZengNature PortfolioNature Communications2041-17232025-07-0116111410.1038/s41467-025-60502-0BIGFAM - variance components analysis from relatives without genotypeJaeeun Jerry Lee0Buhm Han1Interdisciplinary Program in Bioengineering, Seoul National UniversityInterdisciplinary Program in Bioengineering, Seoul National UniversityAbstract Estimating variance components of phenotypes provides a fundamental basis for understanding complex traits. However, most existing methods require genotype data, which is costly to obtain and often unavailable, limiting their scalability. To address this limitation, we developed BIGFAM, a genotype-free framework that estimates variance components by genetic, shared environmental, and X chromosome effects using only phenotype data from relative pairs. We analyze variance components in Generation Scotland and UK Biobank datasets and demonstrate that BIGFAM’s estimates show high correlation with genotype-based methods ( $$r$$ r  = 0.85 for heritability and 0.64 for X chromosome components). We identify strong nuclear-family-specific shared environmental effects in dietary-related phenotypes. These results establish a new approach for analyzing variance components across diverse populations without the need for genetic data.https://doi.org/10.1038/s41467-025-60502-0
spellingShingle Jaeeun Jerry Lee
Buhm Han
BIGFAM - variance components analysis from relatives without genotype
Nature Communications
title BIGFAM - variance components analysis from relatives without genotype
title_full BIGFAM - variance components analysis from relatives without genotype
title_fullStr BIGFAM - variance components analysis from relatives without genotype
title_full_unstemmed BIGFAM - variance components analysis from relatives without genotype
title_short BIGFAM - variance components analysis from relatives without genotype
title_sort bigfam variance components analysis from relatives without genotype
url https://doi.org/10.1038/s41467-025-60502-0
work_keys_str_mv AT jaeeunjerrylee bigfamvariancecomponentsanalysisfromrelativeswithoutgenotype
AT buhmhan bigfamvariancecomponentsanalysisfromrelativeswithoutgenotype