Proteomics signature of physical activity and risk of multimorbidity of cancer and cardiometabolic diseases
Stein, M. J.; Baurecht, H.; Bohmann, P.; Cordova, R.; Ferrari, P.; Fervers, B.; Friedenreich, C. M.; Gunter, M. J.; Peruchet-Noray, L.; Wu, D.; Leitzmann, M. F.; Viallon, V.; Freisling, H.
Show abstract
BackgroundCancer, cardiovascular diseases (CVD), and type 2 diabetes (T2D) may co-occur, a condition referred to as multimorbidity. Physical activity is inversely associated with each of these diseases; however, the biologic pathways underlying these relationships remain incompletely understood. MethodsIn 33,806 UK Biobank participants, we derived a proteomic signature (high-throughput panel of 2,911 proteins assessed by Olink array) of moderate-to-vigorous physical activity using linear and LASSO regressions in a two-step procedure to prospectively assess associations with physical activity-related cancers (1,108 cases), CVD (3,445 cases), T2D (1,363 cases), as well as progression to multimorbidity (420 cases). Multivariable Cox regression estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for each identified protein, as well as their linear combination (proteomics signature score), separately for each outcome and with adjustment for physical activity. Pathway enrichment analysis and protein-protein interaction networks were used to gain insights into the systemic interplay of the identified proteins. ResultsAfter correction for multiple testing, 223 proteins were selected in the physical activity signature. Proteins involved in food intake, metabolism, and cell growth regulation (e.g., LEP, MSTN, TGFBR2) were inversely associated with physical activity. Proteins involved in immune cell adhesion and migration, as well as cartilage and muscle integrity (e.g., integrins, COMP, MYOM3) were positively associated with physical activity. Several proteins upregulated by physical activity were inversely associated with disease risk (e.g., integrins, PI3, CLEC4A for cancer risk, or LPL, IGFBP1, LEP for T2D risk). Similarly, various proteins were downregulated by physical activity and positively associated with disease risk (e.g., CD38, TGFA for CVD risk). For multimorbidity, proteins inversely related to physical activity generally aligned with expected risk patterns, while positively associated proteins exhibited mixed effects, with inverse and positive associations. The proteomics signature score was inversely associated with the risk of cancer (HR per interquartile range: 0.87; 95% CI: 0.78, 0.96) and T2D (HR: 0.66; 95% CI: 0.60, 0.72), after adjustment for physical activity, but not with CVD (HR: 0.93; 95% CI: 0.85, 1.03) and progression towards multimorbidity. ConclusionsThese findings suggest that the inverse relationships between physical activity and risk of major chronic diseases may be explained by the maintenance of tissue integrity and the proper regulation of immune and metabolic processes. Further studies are needed to determine the causal nature of these associations.
Matching journals
The top 12 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Environment-wide association study (EWAS) on cardiometabolic traits: A systematic assessment of the association of lifestyle variables on a longitudinal setting 93%
- Modifiable lifestyle factors and genetic risk of obesity in Indians 92%
- Metabolic subgroups and cardiometabolic multimorbidity in the UK Biobank 92%
Similar papers in this journal
- Systematic discovery of gene-environment interactions underlying the human plasma proteome in UK Biobank 93%
- Metabolic and proteomic signatures of type 2 diabetes subtypes in an Arab population 93%
- Twin pair analysis uncovers novel links between DNA methylation, mitochondrial DNA quantity and obesity 93%
Similar papers in this journal
- Pervasive Influence of Hormonal Contraceptives on the Human Plasma Proteome in a Broad Population Study 91%
- The Interpretable Multimodal Machine Learning (IMML) framework reveals pathological signatures of distal sensorimotor polyneuropathy 90%
- Deep plasma proteomics identifies and validates an eight-protein biomarker panel that separate benign from malignant tumors in ovarian cancer 90%
Similar papers in this journal
- Predictive value of circulating NMR metabolic biomarkers for type 2 diabetes risk in the UK Biobank study 93%
- Risk of cancer in regular and low meat-eaters, fish-eaters, and vegetarians: a prospective analysis of UK Biobank participants 92%
- Adults prenatally exposed to the Dutch Famine exhibit a metabolic signature associated with a broad spectrum of common diseases 92%
Similar papers in this journal
- Distinct metabolic features of genetic liability to type 2 diabetes and coronary artery disease: a reverse Mendelian randomization study 92%
- 1 H-NMR metabolomics-based surrogates to impute common clinical risk factors and endpoints 92%
- Association between circulating inflammatory markers and adult cancer risk: a Mendelian randomization analysis 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.