Background
Worldwide obesity affects about 700 million adults and the prevalence continues to increase steadily in most countries, including China. Adiposity is associated with multiple diseases and traits, but little is known about the causal relevance and mechanisms underlying these associations. Available evidence on proteomics has been constrained by studies involving relatively small numbers of proteins, or have been restricted to Western populations only. In a proteogenomic study authored by researchers from Oxford University and Peking University, the Olink® Explore platform was used to measure 1463 proteins in 3977 Chinese adult participants in the China Kadoorie Biobank (CKB), with both measured and genetically-instrumented body mass index (BMI) used as proxies for adiposity.
The associations of protein levels with conventional (physically measured) and genetically selected BMIs were determined, and protein quantitative loci (pQTLs) were used in a Mendelian Randomization (MR) analysis to identify proteins causally linked to BMI. The findings were then replicated using data available from the UK Biobank Pharma Proteomics Project (UKB-PPP), in which the same 1436 proteins were measured in >50k individuals of mainly European origin.
Outcome
In the first phase of the study using the CKB samples, 798 proteins were significantly associated with conventionally measured BMI after Bonferroni correction (625 positively, 173 negatively). Using genetically derived BMI analysis, 307 proteins were significant after applying corrections, 279 of which overlapped with the conventional analysis. Both the conventional and genetic associations were broadly linear throughout the range of BMI examined. Pathway enrichment showed that the top 50 proteins were most strongly linked to biological processes such as atherosclerosis, lipid metabolism, tumor progression and inflammation. Using the protein and GWAS data, cis-pQTLs were then identified for 742 proteins and MR analysis indicated 8 proteins causally linked to BMI (ITIH3, LRP11, SCAMP3, NUDT5, OGN, EFEMP1, TXNDC15, and PRDX6).
When the genetically determined BMI-associated proteins from the CKB study were compared to data from the UKB cohort 295/307 (>90%) of the genetic associations were replicated. The effect sizes of the overlapping proteins identified in the two cohorts also showed a high degree of correlation with a p value of 0.86. The causality findings for OGN and TXNDC15 were also replicated in the two cohorts – these proteins may be particularly interesting targets for drug interventions, as they are known to be highly expressed in adipose tissue and liver, respectively.
Overall, this study showed that BMI had a causal effect on expression of ~300 proteins and that 8 proteins showed a causal effect on BMI. The approach also uncovered novel pathways by which adiposity may increase disease risks and identified novel potential drug targets for future therapeutic development. There was good replication of key findings between the CKB and UKB cohorts, despite the genetic divergence of the two populations and a major difference in mean BMI levels and BMI ranges.
