Imputed gene expression risk scores: a functionally informed component of polygenic risk

Oliver Pain; Kylie P. Glanville; Saskia Hagenaars; Saskia Selzam; Anna Fürtjes; Jonathan R.I. Coleman; Kaili Rimfeld; Gerome Breen; Lasse Folkersen; Cathryn M. Lewis

doi:10.1093/hmg/ddab053

Imputed gene expression risk scores: a functionally informed component of polygenic risk

Oliver Pain, Kylie P. Glanville, Saskia Hagenaars, Saskia Selzam, Anna Fürtjes, Jonathan R.I. Coleman, Kaili Rimfeld, Gerome Breen, Lasse Folkersen, Cathryn M. Lewis

Research output: Contribution to journal › Article › peer-review

11 Citations (Scopus)

Abstract

Integration of functional genomic annotations when estimating polygenic risk scores (PRS) can provide insight into aetiology and improve risk prediction. This study explores the predictive utility of gene expression risk scores (GeRS), calculated using imputed gene expression and transcriptome-wide association study (TWAS) results. The predictive utility of GeRS was evaluated using 12 neuropsychiatric and anthropometric outcomes measured in two target samples: UK Biobank and the Twins Early Development Study. GeRS were calculated based on imputed gene expression levels and TWAS results, using 53 gene expression-genotype panels, termed single nucleotide polymorphism (SNP)-weight sets, capturing expression across a range of tissues. We compare the predictive utility of elastic net models containing GeRS within and across SNP-weight sets, and models containing both GeRS and PRS. We estimate the proportion of SNP-based heritability attributable to cis-regulated gene expression. GeRS significantly predicted a range of outcomes, with elastic net models combining GeRS across SNP-weight sets improving prediction. GeRS were less predictive than PRS, but models combining GeRS and PRS improved prediction for several outcomes, with relative improvements ranging from 0.3% for height (P = 0.023) to 4% for rheumatoid arthritis (P = 5.9 × 10-8). The proportion of SNP-based heritability attributable to cis-regulated expression was modest for most outcomes, even when restricting GeRS to colocalized genes. GeRS represent a component of PRS and could be useful for functional stratification of genetic risk. Only in specific circumstances can GeRS substantially improve prediction over PRS alone. Future research considering functional genomic annotations when estimating genetic risk is warranted.

Original language	English
Pages (from-to)	727-738
Number of pages	12
Journal	Human Molecular Genetics
Volume	30
Issue number	8
DOIs	https://doi.org/10.1093/hmg/ddab053
Publication status	Published - 17 May 2021

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@article{95addd99c63e42688ba98287eac35906,

title = "Imputed gene expression risk scores: a functionally informed component of polygenic risk",

abstract = "Integration of functional genomic annotations when estimating polygenic risk scores (PRS) can provide insight into aetiology and improve risk prediction. This study explores the predictive utility of gene expression risk scores (GeRS), calculated using imputed gene expression and transcriptome-wide association study (TWAS) results. The predictive utility of GeRS was evaluated using 12 neuropsychiatric and anthropometric outcomes measured in two target samples: UK Biobank and the Twins Early Development Study. GeRS were calculated based on imputed gene expression levels and TWAS results, using 53 gene expression-genotype panels, termed single nucleotide polymorphism (SNP)-weight sets, capturing expression across a range of tissues. We compare the predictive utility of elastic net models containing GeRS within and across SNP-weight sets, and models containing both GeRS and PRS. We estimate the proportion of SNP-based heritability attributable to cis-regulated gene expression. GeRS significantly predicted a range of outcomes, with elastic net models combining GeRS across SNP-weight sets improving prediction. GeRS were less predictive than PRS, but models combining GeRS and PRS improved prediction for several outcomes, with relative improvements ranging from 0.3% for height (P = 0.023) to 4% for rheumatoid arthritis (P = 5.9 × 10-8). The proportion of SNP-based heritability attributable to cis-regulated expression was modest for most outcomes, even when restricting GeRS to colocalized genes. GeRS represent a component of PRS and could be useful for functional stratification of genetic risk. Only in specific circumstances can GeRS substantially improve prediction over PRS alone. Future research considering functional genomic annotations when estimating genetic risk is warranted.",

author = "Oliver Pain and Glanville, {Kylie P.} and Saskia Hagenaars and Saskia Selzam and Anna F{\"u}rtjes and Coleman, {Jonathan R.I.} and Kaili Rimfeld and Gerome Breen and Lasse Folkersen and Lewis, {Cathryn M.}",

note = "Publisher Copyright: {\textcopyright} 2021 The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: [email protected]. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",

year = "2021",

month = may,

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doi = "10.1093/hmg/ddab053",

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T1 - Imputed gene expression risk scores

T2 - a functionally informed component of polygenic risk

AU - Pain, Oliver

AU - Glanville, Kylie P.

AU - Hagenaars, Saskia

AU - Selzam, Saskia

AU - Fürtjes, Anna

AU - Coleman, Jonathan R.I.

AU - Rimfeld, Kaili

AU - Breen, Gerome

AU - Folkersen, Lasse

AU - Lewis, Cathryn M.

N1 - Publisher Copyright: © 2021 The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: [email protected]. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2021/5/17

Y1 - 2021/5/17

N2 - Integration of functional genomic annotations when estimating polygenic risk scores (PRS) can provide insight into aetiology and improve risk prediction. This study explores the predictive utility of gene expression risk scores (GeRS), calculated using imputed gene expression and transcriptome-wide association study (TWAS) results. The predictive utility of GeRS was evaluated using 12 neuropsychiatric and anthropometric outcomes measured in two target samples: UK Biobank and the Twins Early Development Study. GeRS were calculated based on imputed gene expression levels and TWAS results, using 53 gene expression-genotype panels, termed single nucleotide polymorphism (SNP)-weight sets, capturing expression across a range of tissues. We compare the predictive utility of elastic net models containing GeRS within and across SNP-weight sets, and models containing both GeRS and PRS. We estimate the proportion of SNP-based heritability attributable to cis-regulated gene expression. GeRS significantly predicted a range of outcomes, with elastic net models combining GeRS across SNP-weight sets improving prediction. GeRS were less predictive than PRS, but models combining GeRS and PRS improved prediction for several outcomes, with relative improvements ranging from 0.3% for height (P = 0.023) to 4% for rheumatoid arthritis (P = 5.9 × 10-8). The proportion of SNP-based heritability attributable to cis-regulated expression was modest for most outcomes, even when restricting GeRS to colocalized genes. GeRS represent a component of PRS and could be useful for functional stratification of genetic risk. Only in specific circumstances can GeRS substantially improve prediction over PRS alone. Future research considering functional genomic annotations when estimating genetic risk is warranted.

AB - Integration of functional genomic annotations when estimating polygenic risk scores (PRS) can provide insight into aetiology and improve risk prediction. This study explores the predictive utility of gene expression risk scores (GeRS), calculated using imputed gene expression and transcriptome-wide association study (TWAS) results. The predictive utility of GeRS was evaluated using 12 neuropsychiatric and anthropometric outcomes measured in two target samples: UK Biobank and the Twins Early Development Study. GeRS were calculated based on imputed gene expression levels and TWAS results, using 53 gene expression-genotype panels, termed single nucleotide polymorphism (SNP)-weight sets, capturing expression across a range of tissues. We compare the predictive utility of elastic net models containing GeRS within and across SNP-weight sets, and models containing both GeRS and PRS. We estimate the proportion of SNP-based heritability attributable to cis-regulated gene expression. GeRS significantly predicted a range of outcomes, with elastic net models combining GeRS across SNP-weight sets improving prediction. GeRS were less predictive than PRS, but models combining GeRS and PRS improved prediction for several outcomes, with relative improvements ranging from 0.3% for height (P = 0.023) to 4% for rheumatoid arthritis (P = 5.9 × 10-8). The proportion of SNP-based heritability attributable to cis-regulated expression was modest for most outcomes, even when restricting GeRS to colocalized genes. GeRS represent a component of PRS and could be useful for functional stratification of genetic risk. Only in specific circumstances can GeRS substantially improve prediction over PRS alone. Future research considering functional genomic annotations when estimating genetic risk is warranted.

UR - http://www.scopus.com/inward/record.url?scp=85107083497&partnerID=8YFLogxK

U2 - 10.1093/hmg/ddab053

DO - 10.1093/hmg/ddab053

M3 - Article

C2 - 33611520

AN - SCOPUS:85107083497

SN - 0964-6906

VL - 30

SP - 727

EP - 738

JO - Human Molecular Genetics

JF - Human Molecular Genetics

IS - 8

ER -

Imputed gene expression risk scores: a functionally informed component of polygenic risk

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