Conventional and genetic associations of adiposity with 1463 proteins in relatively lean Chinese adults

Abstract

Adiposity is associated with multiple diseases and traits, but little is known about the causal relevance and mechanisms underlying these associations. Large-scale proteomic profiling, especially when integrated with genetic data, can clarify mechanisms linking adiposity with disease outcomes. We examined the associations of adiposity with plasma levels of 1463 proteins in 3977 Chinese adults, using measured and genetically-instrumented BMI. We further used two-sample bi-directional MR analyses to assess if certain proteins influenced adiposity, along with other (e.g. enrichment) analyses to clarify possible mechanisms underlying the observed associations. Overall, the mean (SD) baseline BMI was 23.9 (3.3) kg/m², with only 6% being obese (i.e. BMI ≥ 30 kg/m²). Measured and genetically-instrumented BMI was significantly associated at FDR < 0.05 with levels of 1096 (positive/inverse: 826/270) and 307 (positive/inverse: 270/37) proteins, respectively, with FABP4, LEP, IL1RN, LSP1, GOLM2, TNFRSF6B, and ADAMTS15 showing the strongest positive and PON3, NCAN, LEPR, IGFBP2 and MOG showing the strongest inverse genetic associations. These associations were largely linear, in adiposity-to-protein direction, and replicated (> 90%) in Europeans of UKB (mean BMI 27.4 kg/m²). Enrichment analyses of the top > 50 BMI-associated proteins demonstrated their involvement in atherosclerosis, lipid metabolism, tumour progression and inflammation. Two-sample bi-directional MR analyses using cis-pQTLs identified in CKB GWAS found eight proteins (ITIH3, LRP11, SCAMP3, NUDT5, OGN, EFEMP1, TXNDC15, PRDX6) significantly affect levels of BMI, with NUDT5 also showing bi-directional association. The findings among relatively lean Chinese adults identified novel pathways by which adiposity may increase disease risks and novel potential targets for treatment of obesity and obesity-related diseases.

Keywords: Body mass index; Drug discovery; East Asians; Mendelian randomization analysis; Obesity; Proteomics.

Fig. 1

Overview of analytic approaches and key findings

Fig. 2

Associations of 1-SD higher BMI with 1463 proteins in conventional and genetic analyses in CKB and comparisons of genetic associations between CKB and UKB. Analyses were adjusted for age, age square, sex, study area, fasting time, ambient temperature, ascertainment status, plate ID, and the first 12 PCs (for genetic analyses only). The dotted lines in a and b indicate multi-testing adjusted threshold for statistical significance with red dots showing significant positive associations and blue dots showing significant inverse associations, with names given for certain selected proteins. The solid black dots in c and d are proteins significantly associated with BMI in both conventional and genetic analyses in CKB (left panel) or in both CKB and UKB (right panel), with names given for certain selected proteins

Fig. 3

Genetic associations of BMI with 20 selected proteins, by OLINK panel. Non-linear MR analyses was used to investigate the shape of the genetic associations. Within each panel, top 5 (4 positive and 1 inverse) BMI-associated proteins were included. Piecewise linear method was used to calculate the estimates (adjusted for age, age squared, sex, and study area [ten groups], ascertainment, plate ID, and 12 national PCs). Each line segment begins where the previous segment finished (black lines) and the intercept was set to the population mean BMI (red dot). The 95% CI are represented by the shaded patterns. The length of y-axis represents approximately ± 2 SD from the mean of the corresponding protein

Fig. 4

Chord diagrams of enriched a GO biological process terms and b KEGG pathways for proteins causally affected by BMI. Enrichment analyses were conducted for 55 proteins that passed Bonferroni-corrected threshold in the genetic analyses (adiposity-to-protein direction), using a GO-BP and b KEGG enrichment analyses. The right semicircle represents the names of a top 10 GO terms and b 8 significant KEGG pathways, and the left semicircle are proteins that are significantly associated with any of the GO terms or KEGG pathways. Proteins were ordered by OLINK panel, and the numbers in brackets represent the number of proteins involved in the GO terms or KEGG pathways