Figures and data
Study overview.
We recruited sedentary men with either normal weight or overweight for deep phenotyping before and after a prolonged exercise intervention. Multi-omic analyses, including serum proteomics, clinical traits and muscle and fat transcriptomics identified changed proteins and potential exerkines. Candidate exerkines were subsequently analyzed in serum samples from the UK biobank and tested for associations with physical activity and glucometabolic traits. Top candidates were then subjected to Mendelian randomization and investigated in a mouse exercise model and in a mouse knock-out model to assess casual links between exerkines and glucometabolic traits.
Serum proteomic responses to prolonged exercise.
(A) A volcano plot showing responses in all participants. The X-axis shows log2(fold-changes) and the Y-axis shows negative log10(Q-values). The red dots indicate statistical significance (Q<0.05). Only the top 3 up/down-regulated proteins are annotated. (B-C) Similar to A, but in normal weight and overweight men only. (D-E) Venn diagrams of the significant change in proteins shown in A-C. NPX = normalized protein expression. Q = P-values corrected using Benjamini-Hochberg’s method. NW = normal weight. OW = overweight.
A serum proteomic liver fat signature.
(A) No up-regulated proteins after prolonged exercise overlapped with known pathways. (B) Only the 66 down-regulated proteins in the OW group overlapped with known pathways. (C) Top 10 gene sets overlapping with these 66 proteins. (D) SLC22A1 is a key driver among these 66 proteins. (E) These 66 proteins overlapped with a known human serum proteomic non-alcoholic fatty liver disease signature from Govaere et al 38. (F) The down-regulated proteins in the OW group were elevated in OW vs. NW at baseline but normalized in the OW group after prolonged exercise. The principal component of these 66 proteins correlated with (G) liver fat content at baseline, but (H) not after prolonged exercise, with (I) the clamp M value at baseline, but (J) not after prolonged exercise. (K) The principal component (PC) of these 66 proteins mediated 36.9% of the association between liver fat and M. (L) The principal component of these 66 proteins correlated with several liver-related markers at baseline, but not after prolonged exercise except for ASAT and ALAT (white = non-significant, red/blue = significant). *p<0.05 and **p<0.01.
Comparison of secretory protein responses to prolonged exercise in blood with corresponding mRNA levels in skeletal muscle and adipose tissue.
(A) mRNA levels in skeletal muscle and (B) adipose tissue for proteins that responded significantly to prolonged exercise. (C) A heatmap of log2(fold-changes) in blood, skeletal muscle and adipose tissue. (D) The most responding mRNA in skeletal muscle, and (E) the response in the blood protein. (F) The most responding mRNA in adipose tissue, and (G) the response in the blood. (H-I) Venn diagrams of significant changes in blood, skeletal muscle and adipose tissue. FC = fold-change. SkM = skeletal muscle. ScWAT = subcutaneous adipose tissue. NPX = normalized protein expression. RPKM = reads per kilobase per million mapped read. *p<0.05, **p<0.01 and ***p<0.001.
Cd300 lg
(A) The response from baseline to week 12 in serum CD300LG and CD300LG mRNA in (B) subcutaneous adipose tissue (ScWAT) and (C) skeletal muscle (SkM). (D) Correlation between the change from before to after prolonged exercise in serum CD300LG and insulin sensitivity. Pathway enrichment analyses were performed on the top 500 most correlated (and p<0.05) genes to the change in serum CD300LG, and only the top 10 pathways with Q<0.05 are presented. *p<0.05, **p<0.01 and ***p<0.001.
Tissue and cell specific expression of CD300LG.
(A) mRNA levels of CD300LG in a human tissue panel (see Methods). (B-C) snRNAseq of human adipose tissue, displaying (B) all detected cell clusters and (C) CD300LG related to the clusters (purple color). (D-E) Similar to B-C, but showing the (D) vascular cell clusters and (E) the corresponding expression of CD300LG (purple color). FPKM = Fragments per kilobase of transcript per million mapped reads. Data were obtained from Uhlen et al. 42 and from Emont et al. 43 and can be explored at https://singlecell.broadinstitute.org/single_cell
Multiple regression analyses between serum CD300LG, and measures of physical activity and glucometabolic traits in the UK biobank.
