Twin Study Provides Heritability Estimates for 2321 Plasma Proteins and Assesses Missing SNP Heritability

Assessing how much variability in blood plasma proteins is due to genetic or environmental factors is essential for advancing personalized medicine. While large-scale studies have established SNP-based heritability (SNP-h<sup>2</sup>) estimates for plasma proteins, less is known about the proportion of total genetic effects on protein variability. We applied quantitative genetic twin models to estimate the heritability of 2321 plasma proteins and to assess the proportion of heritability accounted for by SNP-h<sup>2</sup> estimates. Olink proteomics data were generated for 401 twins aged 56-70, including 196 complete same-sex twin pairs. On average, 40% of protein variability was attributable to genetic effects. Twin-based heritability estimates were highly correlated with published SNP-h<sup>2</sup> estimates from the UK Biobank (Spearman coefficient: ρ = 0.80). However, on average, only half of the total heritability was covered by SNP-h<sup>2</sup>, and the other half, representing one-fifth of the total protein phenotypic variability, remains missing.

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Publication Details

Journal
Journal of Proteome Research
Published
2025-05-27
DOI
https://doi.org/10.1021/acs.jproteome.4c00971
Citations
2
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
3.63
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article

Twin Study Provides Heritability Estimates for 2321 Plasma Proteins and Assesses Missing SNP Heritability

Jaakko A. Kaprio, Gabin Drouard, Fiona A. Hagenbeek, Zhili Zheng et al.
2 citations
Journal of Proteome Research
Genetic Associations and Epidemiology
3.63
article

Twin Study Provides Heritability Estimates for 2321 Plasma Proteins and Assesses Missing SNP Heritability

Jaakko A. Kaprio, Gabin Drouard, Fiona A. Hagenbeek, Zhili Zheng, Matti Pirinen, Xiao-Ling Wang, Miina Ollikainen, Samuli Ripatti
article en
2 citations

Abstract

Assessing how much variability in blood plasma proteins is due to genetic or environmental factors is essential for advancing personalized medicine. While large-scale studies have established SNP-based heritability (SNP-h<sup>2</sup>) estimates for plasma proteins, less is known about the proportion of total genetic effects on protein variability. We applied quantitative genetic twin models to estimate the heritability of 2321 plasma proteins and to assess the proportion of heritability accounted for by SNP-h<sup>2</sup> estimates. Olink proteomics data were generated for 401 twins aged 56-70, including 196 complete same-sex twin pairs. On average, 40% of protein variability was attributable to genetic effects. Twin-based heritability estimates were highly correlated with published SNP-h<sup>2</sup> estimates from the UK Biobank (Spearman coefficient: ρ = 0.80). However, on average, only half of the total heritability was covered by SNP-h<sup>2</sup>, and the other half, representing one-fifth of the total protein phenotypic variability, remains missing.

Journal of Proteome ResearchVol. 24(6)
Broad Institute (US), Statistics Finland (FI), University of Helsinki (FI), Augusta University (US), Prevention Institute (US), FishBase Information and Research Group (PH), Augusta University Health (US), Minerva Foundation (FI), Faculty of Public Health (GB), Institute for Molecular Medicine Finland (FI)
Openalex Percentile: Top 8%
Genetic Associations and Epidemiology
3.63
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