Discovering non-additive heritability using additive GWAS summary statistics
Abstract LD score regression (<jats:monospace>LDSC</jats:monospace>) is a method to estimate narrow-sense heritability from genome-wide association study (GWAS) summary statistics alone, making it a fast and popular approach. In this work, we present interaction-LD score (<jats:monospace>i-LDSC</jats:monospace>) regression: an extension of the original<jats:monospace>LDSC</jats:monospace>framework that accounts for interactions between genetic variants. By studying a wide range of generative models in simulations, and by re-analyzing 25 well-studied quantitative phenotypes from 349,468 individuals in the UK Biobank and up to 159,095 individuals in BioBank Japan, we show that the inclusion of acis-interaction score (i.e., interactions between a focal variant and proximal variants) recovers genetic variance that is not captured by<jats:monospace>LDSC</jats:monospace>. For each of the 25 traits analyzed in the UK Biobank and BioBank Japan,<jats:monospace>i-LDSC</jats:monospace>detects additional variation contributed by genetic interactions. The<jats:monospace>i-LDSC</jats:monospace>software and its application to these biobanks represent a step towards resolving further genetic contributions of sources of non-additive genetic effects to complex trait variation..
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Preprint| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
bioRxiv.org - (2024) vom: 18. Apr. Zur Gesamtaufnahme - year:2024 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Smith, Samuel Pattillo [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| doi: |
10.1101/2022.07.21.501001 |
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| PPN (Katalog-ID): |
XBI036604585 |
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| 520 | |a Abstract LD score regression (<jats:monospace>LDSC</jats:monospace>) is a method to estimate narrow-sense heritability from genome-wide association study (GWAS) summary statistics alone, making it a fast and popular approach. In this work, we present interaction-LD score (<jats:monospace>i-LDSC</jats:monospace>) regression: an extension of the original<jats:monospace>LDSC</jats:monospace>framework that accounts for interactions between genetic variants. By studying a wide range of generative models in simulations, and by re-analyzing 25 well-studied quantitative phenotypes from 349,468 individuals in the UK Biobank and up to 159,095 individuals in BioBank Japan, we show that the inclusion of acis-interaction score (i.e., interactions between a focal variant and proximal variants) recovers genetic variance that is not captured by<jats:monospace>LDSC</jats:monospace>. For each of the 25 traits analyzed in the UK Biobank and BioBank Japan,<jats:monospace>i-LDSC</jats:monospace>detects additional variation contributed by genetic interactions. The<jats:monospace>i-LDSC</jats:monospace>software and its application to these biobanks represent a step towards resolving further genetic contributions of sources of non-additive genetic effects to complex trait variation. | ||
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