Proteomic profiling of low muscle and high fat mass: a machine learning approach in the KORA S4/FF4 study

Recurrent depression predicts high leptin concentrations in patients with coronary artery disease over an 18-months follow-up period: Findings from the prospective multicenter randomized controlled SPIRR-CAD Trial

BACKGROUND

Leptin, an adipokine suspected to play a role in coronary artery disease (CAD), may also be associated with deteriorated mental health. We investigated the prospective impact of recurrent depressed mood (RDM) on heightened plasma leptin levels in CAD patients.

METHODS

Derived from the randomized SPIRR-CAD trial, plasma leptin were measured by the Human Leptin DuoSet ELISA at baseline in 539 patients (including 115 (21.3 %) women and 424 (78.7 %) men) and in 373 participants after 18-months follow up (T3). RDM was based on the clinical course from baseline to follow-up assessed by the Hamilton Depression Rating Scale (HAMD). Multivariate binary logistic regression models identified predictors for heightened leptin at T3.

RESULTS

At baseline, highest leptin level (3rd tertile) was associated with type 2 diabetes (p = 0.009), heart failure symptoms (NYHA III) (p < 0.001), female sex and BMI ≥30 (p < 0.001) but not with age and depression. At study endpoint (T3), RDM was associated with a substantially increased risk of experiencing the highest plasma leptin level (OR 2.92 (95 % CI 1.27-6.75)) followed by increased NT-proBNP (the most prominent indicator of CHF) with an OR of 2.73 (1.22-6.11) - both after adjustment for concurrent factors including weight gain (diff BMI T3-T1) over the study period - the latter accounting for an OR of 1.41 (1.17-1.70).

LIMITATIONS

Findings are limited to people of Caucasian ancestry which prevents being generalized to other ethnicities. Although relying upon a prospective design, reverse causality cannot be excluded but is unlikely.

CONCLUSIONS

In CAD patients, RDM is a significant predictor of heightened leptin -a finding opening room for a new pathway of the psychobiological underpinning of depression on CAD risk.

A Multiomics Assessment of Preoperative Exercise in Pancreatic Cancer Survivors Receiving Neoadjuvant Therapy: A Case Series

To molecularly characterize the impact of exercise on mitigating neoadjuvant treatment (NAT)-induced physical decline in pancreatic ductal adenocarcinoma (PDAC) patients, a multi-omics approach was employed for the analysis of plasma samples before and after a personalized exercise intervention. Consisting of personalized aerobic and resistance exercises, this intervention was associated with significant molecular changes that correlated with improvements in lean mass, appendicular skeletal muscle index (ASMI), and performance in the 400-m walk test (MWT) and sit-to-stand test. These alterations indicated exercise-induced modulation of inflammation and mitochondrial function markers. This case study provides proof-of-principal application for multiomics-based assessments of supervised exercise, thereby supporting this intervention as a feasible and beneficial intervention for PDAC patients to potentially enhance treatment response and patient quality of life. The molecular changes observed here underscore the importance of physical activity in cancer treatment protocols, advocating for the development of accessible multiomics-guided exercise programs for cancer patients.

Proteomic profiling of longitudinal changes in kidney function among middle-aged and older men and women: the KORA S4/F4/FF4 study

BACKGROUND

Due to the asymptomatic nature of the early stages, chronic kidney disease (CKD) is usually diagnosed at late stages and lacks targeted therapy, highlighting the need for new biomarkers to better understand its pathophysiology and to be used for early diagnosis and therapeutic targets. Given the close relationship between CKD and cardiovascular disease (CVD), we investigated the associations of 233 CVD- and inflammation-related plasma proteins with kidney function decline and aimed to assess whether the observed associations are causal.

METHODS

We included 1140 participants, aged 55-74 years at baseline, from the Cooperative Health Research in the Region of Augsburg (KORA) cohort study, with a median follow-up time of 13.4 years and 2 follow-up visits. We measured 233 plasma proteins using a proximity extension assay at baseline. In the discovery analysis, linear regression models were used to estimate the associations of 233 proteins with the annual rate of change in creatinine-based estimated glomerular filtration rate (eGFRcr). We further investigated the association of eGFRcr-associated proteins with the annual rate of change in cystatin C-based eGFR (eGFRcys) and eGFRcr-based incident CKD. Two-sample Mendelian randomization was used to infer causality.

RESULTS

In the fully adjusted model, 66 out of 233 proteins were inversely associated with the annual rate of change in eGFRcr, indicating that higher baseline protein levels were associated with faster eGFRcr decline. Among these 66 proteins, 21 proteins were associated with both the annual rate of change in eGFRcys and incident CKD. Mendelian randomization analyses on these 21 proteins suggest a potential causal association of higher tumor necrosis factor receptor superfamily member 11A (TNFRSF11A) level with eGFR decline.

CONCLUSIONS

We reported 21 proteins associated with kidney function decline and incident CKD and provided preliminary evidence suggesting a potential causal association between TNFRSF11A and kidney function decline. Further Mendelian randomization studies are needed to establish a conclusive causal association.

Colorectal Cancer Chemotherapy Drug Bevacizumab May Induce Muscle Atrophy Through CDKN1A and TIMP4

The muscle in the organism has the function of regulating metabolism. Long-term muscle inactivity or the occurrence of chronic inflammatory diseases are easy to induce muscle atrophy. Bevacizumab is an antiangiogenic drug that prevents the formation of neovascularization by inhibiting the activation of VEGF signaling pathway. It is used in the first-line treatment of many cancers in clinic. Studies have shown that the use of bevacizumab in the treatment of tumors can cause muscle mass loss and may induce muscle atrophy. Based on bioinformatics analysis, this study sought the relationship and influence mechanism between bevacizumab and muscle atrophy. The differences of gene and sample expression between bevacizumab treated group and control group were studied by RNA sequencing. WGCNA is used to find gene modules related to bevacizumab administration and explore biological functions through metascape. Differential analysis was used to analyze the difference of gene expression between the administration group and the control group in different muscle tissues. The key genes timp4 and CDKN1A were obtained through Venn diagram, and then GSEA was used to explore their biological functions in RNA sequencing data and geo chip data. This study studied the role of bevacizumab in muscle through the above methods, preliminarily determined that timp4 and CDKN1A may be related to muscle atrophy, and further explored their functional mechanism in bevacizumab myotoxicity.

Proteomics of the phase angle: Results from the population-based KORA S4 study

BACKGROUND & AIMS

The phase angle (PhA) measured with bioelectrical impedance analysis is considered to reflect the interrelated components body cell mass and fluid distribution based on technical and physical aspects of the PhA measurement. However, the biomedical meaning of the PhA remains vague. Previous studies mainly assessed associations of the PhA with numerous diseases and health outcomes, but few connected protein markers to the PhA. To broaden our understanding of the biomedical background of the PhA, we aimed to explore a proteomics profile associated with the PhA and related biological factors.

METHODS

The study sample encompassed 1484 participants (725 women and 759 men) aged 55-74 years from the population-based Cooperative Health Research in the Region of Augsburg (KORA) S4 study. Proteomics measurements were performed with a proximity extension assay. We employed boosting with stability selection to establish a set of markers that was strongly associated with the PhA from a group of 233 plasma protein markers. We integrated the selected protein markers into a network and enrichment analysis to identify gene ontology (GO) terms significantly overrepresented for the selected PhA protein markers.

RESULTS

Boosting with stability selection identified seven protein markers that were strongly and independently associated with the PhA: N-terminal prohormone brain natriuretic peptide (NT-proBNP), insulin-like growth factor-binding protein 2 (IGFBP2), adrenomedullin (ADM), myoglobin (MB), matrix metalloproteinase-9 (MMP9), protein-glutamine gamma-glutamyltransferase 2 (TGM2), and fractalkine (CX3CL1) [beta coefficient per 1 standard deviation increase in normalized protein expression values on a log 2 scale (95% confidence interval): -0.12 (-0.15, -0.08), -0.13 (-0.17, -0.09), -0.14 (-0.18, -0.10), 0.10 (0.07, 0.14), 0.07 (0.04, 0.10), 0.08 (0.05, 0.11), -0.06 (-0.10, -0.03), respectively]. According to the enrichment analysis, this protein profile was significantly overrepresented in the following top five GO terms: positive regulation of cell population proliferation (p-value: 1.32E-04), extracellular space (p-value: 1.34E-04), anatomical structure formation involved in morphogenesis (p-value: 2.92E-04), regulation of multicellular organismal development (p-value: 5.72E-04), and metal ion homeostasis (p-value: 8.86E-04).

CONCLUSION

Implementing a proteomics approach, we identified six new protein markers strongly associated with the PhA and confirmed that NT-proBNP is a key PhA marker. The main biological processes that were related to this PhA's protein profile are involved in regulating the amount and growth of cells, reinforcing, from a biomedical perspective, the current technical-based consensus of the PhA to reflect body cell mass.

Targeted proteomics of appendicular skeletal muscle mass and handgrip strength in black South Africans: a cross-sectional study

Although appendicular skeletal muscle mass (ASM) and handgrip strength (HGS) are key components of sarcopenia, their underlying biological mechanisms remain poorly understood. We aimed to investigate associations of circulating biomarkers with ASM and HGS in middle-aged black South Africans. This study consisted of 934 black South Africans (469 men and 465 women, aged 41-72 years) from the Middle-aged Soweto cohort. Linear regression models were used to examine relationships between 182 biomarkers (measured with proximity extension assay) and dual-energy X-ray absorptiometry-measured ASM and dynamometer-measured HGS. Age, height, sex, smoking, alcohol, food insecurity, physical activity, visceral adipose tissue, HIV and menopausal status were included as confounders. Regression models showing sex-interactions were stratified by sex. The Benjamini-Hochberg false discovery rate (FDR) was used to control for multiple testing, and FDR-adjusted P values were reported. In the total sample, 10 biomarkers were associated with higher ASM and 29 with lower ASM (P < 0.05). Out of these 39 biomarkers, 8 were also associated with lower HGS (P < 0.05). MMP-7 was associated with lower HGS only (P = 0.011) in the total sample. Sex-interactions (P < 0.05) were identified for 52 biomarkers for ASM, and 6 for HGS. For men, LEP, MEPE and SCF were associated with higher ASM (P < 0.001, = 0.004, = 0.006, respectively), and MEPE and SCF were also associated with higher HGS (P = 0.001, 0.012, respectively). Also in men, 37 biomarkers were associated with lower ASM (P < 0.05), with none of these being associated with lower HGS. Furthermore, DLK-1 and MYOGLOBIN were associated with higher HGS only (P = 0.004, 0.006, respectively), while GAL-9 was associated with lower HGS only (P = 0.005), among men. For women, LEP, CD163, IL6, TNF-R1 and TNF-R2 were associated with higher ASM (P < 0.001, = 0.014, = 0.027, = 0.014, = 0.048, respectively), while IGFBP-2, CTRC and RAGE were associated with lower ASM (P = 0.043, 0.001, 0.014, respectively). No biomarker was associated with HGS in women. In conclusion, most biomarkers were associated with ASM and not HGS, and the associations of biomarkers with ASM and HGS displayed sex-specificity in middle-aged black South Africans. Proteomic studies should examine ASM and HGS individually. Future research should also consider sexual dimorphism in the pathophysiology of sarcopenia for development of sex-specific treatment and diagnostic methods.

Putative Candidate Drug Targets for Sarcopenia-Related Traits Identified Through Mendelian Randomization Analysis of the Blood Proteome

Purpose: The increasing prevalence of sarcopenia remains an ongoing challenge to health care systems worldwide. The lack of treatments encouraged the discovery of human proteomes to find potential therapeutic targets. As one of the major components of the human proteome, plasma proteins are functionally connected with various organs of the body to regulate biological processes and mediate overall homeostasis, which makes it crucial in various complex processes such as aging and chronic diseases. By performing a systematic causal analysis of the plasma proteome, we attempt to reveal the etiological mechanism and discover drug targets for sarcopenia. Methods: By using data from four genome-wide association studies for blood proteins and the UK Biobank data for sarcopenia-related traits, we applied two-sample Mendelian randomization (MR) analysis to evaluate 310 plasma proteins as possible causal mediators of sarcopenia-related traits: appendicular lean mass (ALM) and handgrip strength (right and left). Then we performed a two-sample bidirectional Mendelian randomization analysis for the identified putatively causal proteins to assess potential reverse causality that the trait values may influence protein levels. Finally, we performed phenome-wide MR analysis of the identified putatively causal proteins for 784 diseases to test the possible side effects of these proteins on other diseases. Results: Five plasma proteins were identified as putatively causal mediators of sarcopenia-related traits. Specifically, leukocyte immunoglobulin-like receptor subfamily B member 2 (LILRB2), asporin (ASPN), and contactin-2 (CNTN2) had potential causal effects on appendicular lean mass, and ecto-ADP-ribosyltransferase 4 (ART4) and superoxide dismutase 2 (SOD2) had putative causal effects on the handgrip strength, respectively. None of the five putatively causal proteins had a reverse causality relationship with sarcopenia-related traits, and no side effects on other diseases were identified. Conclusion: We identified five plasma proteins that may serve as putatively potential novel drug targets for sarcopenia. Our study attested to the value of two-sample MR analysis in identifying and prioritizing putatively potential therapeutic targets for complex diseases.

Proteomic profiling of low muscle and high fat mass: a machine learning approach in the KORA S4/FF4 study

BACKGROUND

The coexistence of low muscle mass and high fat mass, two interrelated conditions strongly associated with declining health status, has been characterized by only a few protein biomarkers. High-throughput proteomics enable concurrent measurement of numerous proteins, facilitating the discovery of potentially new biomarkers.

METHODS

Data derived from the prospective population-based Cooperative Health Research in the Region of Augsburg S4/FF4 cohort study (median follow-up time: 13.5 years) included 1478 participants (756 men and 722 women) aged 55-74 years in the cross-sectional and 608 participants (315 men and 293 women) in the longitudinal analysis. Appendicular skeletal muscle mass (ASMM) and body fat mass index (BFMI) were determined through bioelectrical impedance analysis at baseline and follow-up. At baseline, 233 plasma proteins were measured using proximity extension assay. We implemented boosting with stability selection to enable false positives-controlled variable selection to identify new protein biomarkers of low muscle mass, high fat mass, and their combination. We evaluated prediction models developed based on group least absolute shrinkage and selection operator (lasso) with 100× bootstrapping by cross-validated area under the curve (AUC) to investigate if proteins increase the prediction accuracy on top of classical risk factors.

RESULTS

In the cross-sectional analysis, we identified kallikrein-6, C-C motif chemokine 28 (CCL28), and tissue factor pathway inhibitor as previously unknown biomarkers for muscle mass [association with low ASMM: odds ratio (OR) per 1-SD increase in log2 normalized protein expression values (95% confidence interval (CI)): 1.63 (1.37-1.95), 1.31 (1.14-1.51), 1.24 (1.06-1.45), respectively] and serine protease 27 for fat mass [association with high BFMI: OR (95% CI): 0.73 (0.61-0.86)]. CCL28 and metalloproteinase inhibitor 4 (TIMP4) constituted new biomarkers for the combination of low muscle and high fat mass [association with low ASMM combined with high BFMI: OR (95% CI): 1.32 (1.08-1.61), 1.28 (1.03-1.59), respectively]. Including protein biomarkers selected in ≥90% of group lasso bootstrap iterations on top of classical risk factors improved the performance of models predicting low ASMM, high BFMI, and their combination [delta AUC (95% CI): 0.16 (0.13-0.20), 0.22 (0.18-0.25), 0.12 (0.08-0.17), respectively]. In the longitudinal analysis, N-terminal prohormone brain natriuretic peptide (NT-proBNP) was the only protein selected for loss in ASMM and loss in ASMM combined with gain in BFMI over 14 years [OR (95% CI): 1.40 (1.10-1.77), 1.60 (1.15-2.24), respectively].

CONCLUSIONS

Proteomic profiling revealed CCL28 and TIMP4 as new biomarkers of low muscle mass combined with high fat mass and NT-proBNP as a key biomarker of loss in muscle mass combined with gain in fat mass. Proteomics enable us to accelerate biomarker discoveries in muscle research.