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Observational Study
. 2021 Oct;45(10):2221-2229.
doi: 10.1038/s41366-021-00896-1. Epub 2021 Jul 5.

Effects of adiposity on the human plasma proteome: observational and Mendelian randomisation estimates

Lucy J Goudswaard  1   2   3   4 , Joshua A Bell  5   6 , David A Hughes  5   6 , Laura J Corbin  5   6 , Klaudia Walter  7 , George Davey Smith  5   6 , Nicole Soranzo  7   8   9 , John Danesh  7   9   10   11   12   13 , Emanuele Di Angelantonio  9   10   11   12   13 , Willem H Ouwehand  7   8   11   14 , Nicholas A Watkins  14 , David J Roberts  9   15   16 , Adam S Butterworth  9   10   11   12   13 , Ingeborg Hers  17   18 , Nicholas J Timpson  5   6
Affiliations
Observational Study

Effects of adiposity on the human plasma proteome: observational and Mendelian randomisation estimates

Lucy J Goudswaard et al. Int J Obes (Lond). 2021 Oct.

Abstract

Background: Variation in adiposity is associated with cardiometabolic disease outcomes, but mechanisms leading from this exposure to disease are unclear. This study aimed to estimate effects of body mass index (BMI) on an extensive set of circulating proteins.

Methods: We used SomaLogic proteomic data from up to 2737 healthy participants from the INTERVAL study. Associations between self-reported BMI and 3622 unique plasma proteins were explored using linear regression. These were complemented by Mendelian randomisation (MR) analyses using a genetic risk score (GRS) comprised of 654 BMI-associated polymorphisms from a recent genome-wide association study (GWAS) of adult BMI. A disease enrichment analysis was performed using DAVID Bioinformatics 6.8 for proteins which were altered by BMI.

Results: Observationally, BMI was associated with 1576 proteins (P < 1.4 × 10-5), with particularly strong evidence for a positive association with leptin and fatty acid-binding protein-4 (FABP4), and a negative association with sex hormone-binding globulin (SHBG). Observational estimates were likely confounded, but the GRS for BMI did not associate with measured confounders. MR analyses provided evidence for a causal relationship between BMI and eight proteins including leptin (0.63 standard deviation (SD) per SD BMI, 95% CI 0.48-0.79, P = 1.6 × 10-15), FABP4 (0.64 SD per SD BMI, 95% CI 0.46-0.83, P = 6.7 × 10-12) and SHBG (-0.45 SD per SD BMI, 95% CI -0.65 to -0.25, P = 1.4 × 10-5). There was agreement in the magnitude of observational and MR estimates (R2 = 0.33) and evidence that proteins most strongly altered by BMI were enriched for genes involved in cardiovascular disease.

Conclusions: This study provides evidence for a broad impact of adiposity on the human proteome. Proteins strongly altered by BMI include those involved in regulating appetite, sex hormones and inflammation; such proteins are also enriched for cardiovascular disease-related genes. Altogether, results help focus attention onto new proteomic signatures of obesity-related disease.

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Conflict of interest statement

JD sits on the International Cardiovascular and Metabolic Advisory Board for Novartis (since 2010); the Steering Committee of UK Biobank (since 2011); the MRC International Advisory Group (ING) member, London (since 2013); the MRC High Throughput Science ‘Omics Panel Member, London (since 2013); the Scientific Advisory Committee for Sanofi (since 2013); the International Cardiovascular and Metabolism Research and Development Portfolio Committee for Novartis; and the Astra Zeneca Genomics Advisory Board (2018).

Figures

Fig. 1
Fig. 1. Strongest BMI and protein Mendelian randomisation associations with corresponding observational associations.
Forest plot of MR results of BMI and protein traits based on P < 1.4 × 10−5 and their corresponding observational estimates.
Fig. 2
Fig. 2. Observational and Mendelian Randomisation estimates show a positive association.
A Scatter plot of the unadjusted (age and sex adjusted) observational estimates and the confounder-adjusted observational estimates for BMI and protein traits with a regression line (blue). B Scatter plot of the unadjusted (age and sex adjusted) observational estimates and the MR estimates for BMI and protein traits with a regression line (blue).
See this image and copyright information in PMC

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