Twin study provides heritability estimates for 2,321 plasma proteins and assesses missing SNP heritability
Drouard, G.; Hagenbeek, F. A.; Ollikainen, M.; Zheng, Z.; Wang, X.; FinnGen, ; Ripatti, S.; Pirinen, M.; Kaprio, J.
Show abstract
Assessing how much of the 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-h2) 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 2,321 plasma proteins and to assess the proportion of heritability accounted for by SNP-h2 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-h2 estimates from the UK Biobank (Spearman coefficient: r=0.80). However, on average, only half of the total heritability was covered by SNP-h2, and the other half, representing one-fifth of total protein phenotypic variability, remains missing.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Pathway-specific polygenic scores substantially increase the discovery of gene-adiposity interactions impacting liver biomarkers 92%
- Large-scale brainstem neuroimaging and genetic analyses provide new insights into the neuronal mechanisms of hypertension 91%
- An LDLR missense variant poses high risk of familial hypercholesterolemia in 30% of Greenlanders and offers potential for early cardiovascular disease intervention 90%
Similar papers in this journal
Similar papers in this journal
- Protein associations and protein–metabolite interactions with depressive symptoms and the p-factor 93%
- Metabolic signature of the pathogenic 22q11.2 deletion identifies carriers and provides insight into systemic dysregulation 92%
- The circulating proteome and brain health: Mendelian randomisation and cross-sectional analyses 90%
Similar papers in this journal
- Dataset on the mass spectrometry-based proteomic profiling of mouse embryonic fibroblasts from a wild type and DYT-TOR1A mouse model of dystonia, basally and during stress 88%
- Curated and harmonised transcriptomics datasets of interstitial lung diseases 85%
- Dataset of the construction and characterization of stable biological nanoparticles 85%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.