Biomarkers of Metabolism and Inflammation in Individuals with Obesity and Normal Weight: A Comparative Analysis Exploring Sex Differences

Abstract

Blood-based biomarkers allow monitoring of an individual's health status and provide insights into metabolic and inflammatory processes in conditions like obesity, cardiovascular, and liver diseases. However, selecting suitable biomarkers and optimizing analytical assays presents challenges, is time-consuming and laborious. Moreover, knowledge of potential sex differences remains incomplete as research is often carried out in men. This study aims at enabling researchers to make informed choices on the type of biomarkers, analytical assays, and dilutions being used. More specifically, we analyzed plasma concentrations of >90 biomarkers using commonly available ELISA or electrochemiluminescence-based multiplex methods, comparing normal weight (BMI < 25; n = 40) with obese (BMI > 30; n = 40) adult blood donors of comparable age. To help choose optimal biomarker sets, we grouped frequently employed biomarkers into biological categories (e.g., adipokines, acute-phase proteins, complement factors, cytokines, myokines, iron metabolism, vascular inflammation), first comparing normal-weight with obese persons, and thereafter exploratively comparing women and men within each BMI group. Many biomarkers linked to chronic inflammation and dysmetabolism were elevated in persons with obesity, including several adipokines, interleukins, chemokines, acute-phase proteins, complement factors, and oxidized LDL. Further exploration suggests sex disparities in biomarker levels within both normal-weight and obese groups. This comprehensive dataset of biomarkers across diverse biological domains constitutes a reference resource that may provide valuable guidance for researchers in selecting appropriate biomarkers and analytical assays for own studies. Moreover, the dataset highlights the importance of taking possible sex differences into account.

Keywords: immunoassays; metabolic risk factors; obesity; sex differences.

Figure 1

Overview of analyzed biomarkers. Biomarkers were clustered based on the organ or the biological process they are typically associated with in the literature. Notably, most of these biomarkers are not very organ-specific and may thus be expressed by several organs at the same time, at different rates. Biomarkers that are ubiquitously expressed or that cannot be linked to a particular process were omitted. Abbreviations (in alphabetical order): ACE, angiotensin converting enzyme; ADAMTS13, a disintegrin and metalloproteinase with thrombospondin motifs 13; ALT, alanine aminotransferase; AST, aspartate aminotransferase; BDNF, brain-derived neurotrophic factor; CCL5, C-C motif chemokine ligand 5 (also referred to as RANTES); CRP, C-reactive protein; CD14, cluster of differentiation 14; CXCL, C-X-C motif chemokine ligand; EPO, erythropoietin; FGF21, fibroblast growth factor 21; IFN-γ, interferon-gamma; IL, interleukin; IL-1Ra, interleukin-1 receptor antagonist; IGF2, insulin growth factor 2; IGFBP7, insulin growth factor binding protein 7; LPS-BP, LPS binding protein; MCP-1, monocyte chemoattractant protein-1; MIF, macrophage migration inhibitory factor; MPO, myeloperoxidase; NF-light, neurofilament light chain; PAI-1, plasminogen activator inhibitor-1; S100B, S100 calcium-binding protein B; SAA, serum amyloid A; TfR, transferrin receptor; sICAM-1, soluble intracellular cell adhesion molecule-1; TIMP-1, tissue inhibitor of metalloproteinases-1; sVCAM-1, soluble vascular cell adhesion molecule-1; TGF-beta, transforming growth factor-beta; TNF-α, tumour necrosis factor-alpha; TNFRII, tumour necrosis factor receptor II; vWF, van Willebrand factor.

Figure 2

Obesity-associated differences in circulating biomarkers independent of sex. Volcano plot of biomarkers in obese vs. normal-weight persons. (A) Positive (or negative) log fold change (Log2FC) means that the respective biomarker is increased (or decreased). Blue dots refer to biomarkers that were significantly differentially expressed in all obese vs. all normal-weight persons, as illustrated by adiponectin, globulin, and leptin. Black dots refer to biomarkers that did not significantly differ comparing all obese vs. all normal-weight persons. (B) List of the top 20 significant biomarkers (−log p-value), the arrows indicate whether a particular biomarker is increased or decreased in obese compared to normal-weight persons. Abbreviations (in alphabetical order): ADAMTS13 = a disintegrin and metalloproteinase with thrombospondin motifs 13; ALT = alanine transaminase; CRP = C-reactive protein; LDH = lactate dehydrogenase; oxLDL = oxidized low-density lipoprotein; SAA = serum amyloid A; SDF-1a = stromal cell-derived factor 1 alpha; THSB4 = thrombospondin-4.

Figure 3

Sex-specific differences in biomarker regulation visualized in a correlation plot. (A) Sex-specific changes in biomarker levels in which the y-axis is the log fold change in a biomarker in obese women vs. normal-weight women (Log2FC_women). Similarly, the x-axis represents the log fold change in a biomarker in obese men vs. normal-weight men (Log2FC_men). Biomarkers similar in women and men fall directly onto the linear regression line, whereas biomarkers with an offset from the linear regression line behave differently in women and men, suggesting dissimilar regulation in the two sexes. A selection of biomarkers is indicated, along with their names. (B) The top 13 significant biomarkers were sorted on strongest absolute difference between obese and normal-weight individuals in men and women as delta log fold change on the x-axis. To generate the graphs, biomarker expression values were plotted, and Pearson regression analysis was performed to obtain the correlation coefficient r. Abbreviations of biomarkers (in alphabetical order): ADAMTS13 = a disintegrin and metalloproteinase with thrombospondin motifs 13; ANGTPL4 = angiopoietin like-4; CK = creatine kinase; Hp = haptoglobin; IL-1 beta = interleukin-1beta; LGALS1 = galectin 1; LPTN = leptin; MIP-1alpha = macrophage inflammatory protein-1 alpha (or CCL3); MSTN = myostatin; PAI-1 = plasminogen activator inhibitor-1; SDF-1a = stromal cell-derived factor 1 alpha; TfR = transferrin receptor.