Longitudinal multi-omics study reveals common etiology underlying association between plasma proteome and BMI trajectories in adolescent and young adult twins

Abstract

Background: The influence of genetics and environment on the association of the plasma proteome with body mass index (BMI) and changes in BMI remain underexplored, and the links to other omics in these associations remain to be investigated. We characterized protein-BMI trajectory associations in adolescents and adults and how these connect to other omics layers. Methods: Our study included two cohorts of longitudinally followed twins: FinnTwin12 (N=651) and the Netherlands Twin Register (NTR) (N=665). Follow-up comprised four BMI measurements over approximately 6 (NTR: 23-27 years old) to 10 years (FinnTwin12: 12-22 years old), with omics data collected at the last BMI measurement. BMI changes were calculated using latent growth curve models. Mixed-effects models were used to quantify the associations between the abundance of 439 plasma proteins with BMI at blood sampling and changes in BMI. The sources of genetic and environmental variation underlying the protein abundances were quantified using twin models, as were the associations of proteins with BMI and BMI changes. In NTR, we investigated the association of gene expression of genes encoding proteins identified in FinnTwin12 with BMI and changes in BMI. We linked identified proteins and their coding genes to plasma metabolites and polygenic risk scores (PRS) using mixed-effect models and correlation networks. Results: We identified 66 and 14 proteins associated with BMI at blood sampling and changes in BMI, respectively. The average heritability of these proteins was 35%. Of the 66 BMI-protein associations, 43 and 12 showed genetic and environmental correlations, respectively, including 8 proteins showing both. Similarly, we observed 6 and 4 genetic and environmental correlations between changes in BMI and protein abundance, respectively. S100A8 gene expression was associated with BMI at blood sampling, and the PRG4 and CFI genes were associated with BMI changes. Proteins showed strong connections with many metabolites and PRSs, but we observed no multi-omics connections among gene expression and other omics layers. Conclusions: Associations between the proteome and BMI trajectories are characterized by shared genetic, environmental, and metabolic etiologies. We observed few gene-protein pairs associated with BMI or changes in BMI at the proteome and transcriptome levels.

Lifestyle differences between co-twins are associated with decreased similarity in their internal and external exposome profiles

“…Samples were first analyzed by independent data acquisition LC-MS/MS using a Q Exactive HF mass spectrometer and further analyzed using Spectronaut software. Data was locally normalized (Callister et al, 2006), and raw matrix counts were processed and quality controlled as described elsewhere (Drouard et al, 2023). Briefly, protein levels were log 2 -transformed and proteins with >10% missing values were excluded.…”

“…Consequently, the emergence of multi-omics studies in twin cohorts is challenged by high-dimensional designs. Multi-omics studies in twins are yet expected to improve our understanding of common traits (Hagenbeek et al, 2023), as was shown in few studies of mental health (Zhu et al, 2019), behavior (Hagenbeek et al, 2023), or body weight (Drouard et al, 2023; Bondia-Pons et al, 2014).…”

Twin study provides heritability estimates for 2,321 plasma proteins and assesses missing SNP heritability

“…One twin study 9 has been conducted to quantify the heritability of blood proteins, but the sample size (36 MZ and 22 DZ twin pairs) and the number of proteins examined (N=342) were limited. Other twin studies have quanti ed protein heritability only for proteins associated with speci c traits 10,11 , but, to our knowledge, no twin study has quanti ed protein heritability across a large number of proteins in the proteome in moderate-to-large samples.…”