henhaobio
Sign in

medRxivGenetic & Genomic MedicinePreprint

Exploring sex-specific causal links between thousands of proteins and lipid metabolism using the UK Biobank Pharma proteomics data.

Daniela ZanettiiD, Mine KopruluiD, Fabiana GrossoiD, Daria V. ZhernakovaiD, Francesca CrobuiD, Serena SannaiD

PDFDOI

Abstract

Lipid traits are known to be sex-differential, but the underlying molecular players are largely unknown. Since protein levels are downstream products of gene expression, proteomics data can be crucial to understand etiology of sex-differences in lipids metabolism. We used sex-specific pQTL summary statistics for 2,923 circulating proteins measured in the UK Biobank Pharma Proteomics Project, along with sex-specific summary statistics of lipids from the Global Lipids Genetics Consortium. We combined these using two-sample Mendelian Randomization analyses and applied stringent multiple testing p-values correction and sensitivity analyses. We identified several sex-specific significant causal links between protein levels and lipid phenotypes: 82 were exclusive to females and 82 to males. The estimated causal effect was instead significant in both sexes but substantially different in size for 38 causal relationships (p <0.05). In the Lifelines Cohort, we replicated 16 sex-specific causal relationships and 4 sex-differentiated relationships also including GWASs restricted to non-statin users, ruling out the potential confounding of lipid-lowering medications more often prescribed in males. Intriguingly, several of these proteins were previously shown to be involved in inflammation and cardiometabolic disease, such as Apolipoprotein(a) and lipoprotein lipase. These results provide insight into potential genetic drivers of sex dimorphism in lipid metabolism.

Citations
1

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISKanoni '22Barupal '19Flynn '20Tomasi '26Zhang '24Koprulu '24
65% semantic matchGenetic & Genomic Medicine
Stavroula Kanoni, Sarah E. Graham, Yuxuan Wang+97 more·Genome biology·Dec 27, 2022· 61 citations