Obesity-related proteins score as a potential marker of breast cancer risk

Biological Markers of Musculoskeletal Pain: A Scoping Review

Background

Musculoskeletal pain (MSP) is the leading contributor to disability, limiting mobility and dexterity. As research on the determinants of MSP is evolving, biomarkers can probably play a significant role in understanding its causes and improving its clinical management. This scoping review aimed to provide an overview of the associations between biomarkers and MSP.

Methods

This study followed Arksey and O'Malley and PRISMA-ScR recommendations. Keywords related to biomarkers, association, and MSP were searched on PubMed, Embase, Cochrane, and Web of Science databases from inception to September 28th, 2023. Data were systematically retrieved from the retained articles. A narrative synthesis approach - but no quality assessment - was used to map the core themes of biological markers of MSP that emerged from this work.

Results

In total, 81 out of 25,165 identified articles were included in this scoping review. These studies were heterogeneous in many aspects. Overall, vitamin D deficiency, dyslipidemia (or hypercholesterolemia), and cytokines (high levels) were the most studied biomarkers with regards to MSP and were most often reported to be associated with non-specific MSP. Cadmium, calcium, C-reactive protein, collagen, creatinine, hormones, omega-3 fatty acids, sodium, tumor necrosis factor-alpha, and vitamin C were also reported to be associated with MSP syndromes, but the evidence on these associations was sketchier. No conclusions could be drawn as to age and sex.

Conclusions

Our findings suggest that some biomarkers are associated with specific MSP syndromes, while others would be associated with non-specific syndromes. Among all candidate markers, the evidence seems to be more consistent for vitamin D, cytokines and lipids (total cholesterol, triglycerides, low- and high-density lipoproteins). High-quality studies, stratified by age and sex, are needed to advance our understanding on biomarkers of MSP.

Obesity, dysbiosis and inflammation: interactions that modulate the efficacy of immunotherapy

Recent years have seen an outstanding growth in the understanding of connections between diet-induced obesity, dysbiosis and alterations in the tumor microenvironment. Now we appreciate that gut dysbiosis can exert important effects in distant target tissues via specific microbes and metabolites. Multiple studies have examined how diet-induced obese state is associated with gut dysbiosis and how gut microbes direct various physiological processes that help maintain obese state in a bidirectional crosstalk. Another tightly linked factor is sustained low grade inflammation in tumor microenvironment that is modulated by both obese state and dysbiosis, and influences tumor growth as well as response to immunotherapy. Our review brings together these important aspects and explores their connections. In this review, we discuss how obese state modulates various components of the breast tumor microenvironment and gut microbiota to achieve sustained low-grade inflammation. We explore the crosstalk between different components of tumor microenvironment and microbes, and how they might modulate the response to immunotherapy. Discussing studies from multiple tumor types, we delve to find common microbial characteristics that may positively or negatively influence immunotherapy efficacy in breast cancer and may guide future studies.

Increases in BMI contribute to worsening inflammatory biomarkers related to breast cancer risk in women: a longitudinal study

BACKGROUND

Inflammatory adipokines and cytokines play a pivotal role in linking obesity and breast cancer (BC) risk in women. We investigated the longitudinal associations between BMI change and trajectories of inflammatory biomarkers related to BC risk.

METHODS

A longitudinal study was conducted among 442 Chinese women with 3-year repeated measures from 2019 to 2021. Plasma circulating inflammatory biomarkers related to BC risk, including adiponectin (ADP), resistin (RETN), soluble leptin receptor (sOB-R), insulin-like growth factor-binding protein-3 (IGFBP-3), and C-reactive protein (CRP), were examined annually. Linear mixed-effect models (LMM) were applied to investigate associations of time-varying BMI with trajectories of biomarkers. We additionally examined the modification effect of baseline BMI groups, menopausal status, and metabolic syndrome.

RESULTS

BMI was associated with increased levels of RETN, CRP, sOB-R, and decreased levels of ADP at baseline. An increasing BMI rate was significantly associated with an average 3-year increase in RETN (β = 0.019, 95% CI 0.004 to 0.034) and sOB-R (β = 0.022, 95% CI 0.009 to 0.035), as well as a decrease in ADP (β =  - 0.006, 95% CI  - 0.012 to 0.001). These associations persisted across different baseline BMI groups. An increasing BMI rate was significantly associated with an average 3-year increase in CRP levels among normal weight (β = 0.045, 95% CI 0.001 to 0.088) and overweight (β = 0.060, 95% CI 0.014 to 0.107) women. As BMI increased over time, a more remarkable decrease in ADP was observed among women with metabolic syndrome (β =  - 0.016, 95% CI - 0.029 to - 0.004) than those without metabolic syndrome at baseline.

CONCLUSIONS

A higher increase rate of BMI was associated with poorer trajectories of inflammatory biomarkers related to BC risk. Recommendations for BMI reduction may benefit BC prevention in women, particularly for those with metabolic syndrome.

[Association of Body Mass Index and Weight Gain With Obesity-Related Breast Cancer Risk Biomarkers in Adult Chinese Women]

Objective

To investigate the associatiojn of body mass index (BMI) at different stages of life and weight gain in adulthood with obesity-related breast cancer risk biomarkers and to provide evidence for formulating policies concerning the prevention and control of breast cancer.

Methods

A cross-sectional study was designed based on the follow-up cohort of southwest China community-based breast cancer screening of women. Using sequential sampling, eligible participants were enrolled from the cohort as the subjects of the study. Information on the basic risk factors was collected and the height, weight, and plasma biomarker levels were measured. Multiple linear regression model was applied to analyze the associations of early adulthood BMI (defined as the BMI of the participant at age 20), adulthood BMI (defined as the BMI measured at the time of enrollment), and weight gain in adulthood with the biomarkers. The concentrations of the biomarkers were incorporated in the model after log transformation.

Results

The average age of the 442 participants was 49 (45, 54) years old, the average early adulthood BMI and adulthood BMI were 21.47 (19.56, 23.11) and 24.10 (22.59, 25.97) kg/m 2, respectively, and the average weight gain in adulthood was 6.60 (2.00, 11.00) kg. Adulthood BMI was negatively associated with adiponectin level ( β=-0.026, 95% CI: -0.045--0.008, P=0.006), and positively associated with C-reactive protein level ( β=0.095, 95% CI: 0.054-0.137, P<0.001) and leptin receptor level ( β=0.090, 95% CI: 0.063-0.117, P<0.001). No association was found between adulthood BMI and resistin levels or between adulthood BMI and insulin-like growth factor-binding protein-3 levels. BMI in early adulthood was found to be negatively associated with only insulin-like growth factor-binding protein-3 levels ( β=-0.039, 95% CI: -0.068--0.010, P=0.009). Further analysis of adulthood weight gain after the age of 20 revealed that average annual weight gain in adulthood was negatively associated with adiponectin levels and positively associated with 4 other biomarkers. Furthermore, compared with those of women whose weight remained stable, the adiponectin level of women whose weight gain in adulthood exceeded 5.00 kg was much lower ( β=-0.185, 95% CI: -0.320--0.049, P=0.008), while their insulin-like growth factor-binding protein-3 ( β=0.389, 95% CI: 0.183-0.594, P<0.001) and leptin receptor ( β=0.245, 95% CI: 0.048-0.442, P=0.015) levels were higher.

Conclusion

Weight gain in adulthood is strongly associated with the changes in obesity-related breast cancer risk biomarkers. Women should maintain a stable weight throughout adulthood and it is preferred that their weight gain should not exceed 5.00 kg.

Temporal relationships between BMI and obesity-related predictors of cardiometabolic and breast cancer risk in a longitudinal cohort

Prospective inter-relationships among biomarkers were unexplored, which may provide mechanistic insights into diseases. We investigated the longitudinal associations of BMI change with trajectories of biomarkers related to cardiometabolic or breast cancer risk. A longitudinal study was conducted among 444 healthy women between 2019 to 2021. Cross‑lagged path analysis was used to examine the temporal relationships among BMI, cardiometabolic risk score (CRS), and obesity‑related proteins score (OPS) of breast cancer. Linear mixed-effect models were applied to investigate associations of time-varying BMI with biomarker-based risk score trajectories. Baseline BMI was associated with subsequent change of breast cancer predictors (P = 0.03), and baseline CRS were positively associated with OPS change (P < 0.001) but not vice versa. After fully adjustment of confounders, we found a 0.058 (95%CI = 0.009-0.107, P = 0.020) units increase of CRS and a 1.021 (95%CI = 0.041-1.995, P = 0.040) units increase of OPS as BMI increased 1 kg/m² per year in postmenopausal women. OPS increased 0.784 (95%CI = 0.053-1.512, P = 0.035) units as CRS increased 1 unit per year. However, among premenopausal women, BMI only significantly affected CRS (β = 0.057, 95%CI = 0.007 to 0.107, P = 0.025). No significant change of OPS with time-varying CRS was found. Higher increase rates of BMI were associated with worse trajectories of biomarker-based risk of cardiometabolic and breast cancer. The longitudinal impact of CRS on OPS is unidirectional. Recommendations such as weight control for the reduction of cardiometabolic risk factors may benefit breast cancer prevention, especially in postmenopausal women.

Associations between changes of smartphone pedometer-assessed step counts and levels of obesity-related breast cancer biomarkers in non-cancer women: A population-based observational study

While a higher level of physical activity (PA) is inversely associated with a higher breast cancer (BC) risk, the health benefits of daily steps on obesity-related BC biomarkers remain unclear. We aimed to understand the associations of changes in step counts with levels of five obesity-related BC biomarkers during a two-year follow-up. In total, 144 non-cancer women (47.96 ± 5.72) were observed on both 2019 and 2021. A structured questionnaire, daily steps and fasting blood samples were collected before (t0, 2019) and after (t1, 2021). Levels of biomarkers (IGF-binding proteins 3, adiponectin, soluble leptin receptor, C-reactive protein, and resistin) were assayed by ELISA. Participants were divided into persistent low steps, decreasing steps, increasing steps, and persistent high steps. Associations of categories on proposed biomarkers were estimated using linear regression models, with persistent low steps as reference. Associations between time-varying step counts with biomarkers were quantified using mixed linear models. Compared with persistent low steps, increasing steps is associated with a reduction in C-reactive protein level (β=-0.74, 95%CI=-1.23--0.26, P-value = 2.98 × 10-3). An inverse association between time-varying step counts with C-reactive protein level was identified, consistent across different obesity types and baseline step level categories. No association with daily step counts was observed for other proteins.

[Effect of Interactions Among Obesity-Related Proteins on Breast Cancer Risk: A Preliminary Study]

Objective

To explore the potential interactions among obesity-related proteins in the pathogenic process of breast cancer (BC) in women.

Methods

We conducted a case-control study, enrolling 279 primary breast cancer cases and 260 age-frequency-matched healthy women between April 2014 and May 2015. Based on the evidence of previous published literature on obesity-related proteins and BC risks, we selected proteins that received more attention and measured the plasma levels of these proteins by enzyme-linked immunosorbent assay (ELISA). After stratification of the subjects according to their menopausal status, an analytic strategy combining multivariate logistic regression and generalized multifactor dimensionality reduction (GMDR) was used to explore the effect of the possible interactions of these proteins on BC risk.

Results

There were marginal high-order interactions among insulin-like growth factor 1 (IGF-1), insulin-like growth factor binding protein 3 (IGFBP-3), C-reactive protein (CRP), resistin (RETN), soluble leptin receptor (sOB-R), and adiponectin (ADP) in premenopausal women (with the balanced accuracy for the testing set being 59.01%, cross-validation consistency being 10/10, and permutation test P=0.05). There were high-order interactions among leptin (LEP), sOB-R, ADP, CRP, IGFBP3 and visfatin (VF) in postmenopausal women (with the balanced accuracy for the testing set being 67.31%, cross-validation consistency being 10/10, and permutation test P=0.01). Along with an increase in the number of obesity-related proteins to which the subjects were exposed, the risk of developing breast cancer gradually increased in both pre- and postmenopausal women ( OR pre =2.18, 95% CI: 1.69-2.82; OR post =2.41, 95% CI: 1.75-3.32).

Conclusions

This preliminary study suggested high-order interactions among obesity-related proteins on BC risk in both pre- and postmenopausal women. In future studies, close attention should be given to these potential interactions when these proteins are used jointly as predictors, as well as in developing a comprehensive risk scoring system for BC.

Intergenic SNPs in Obstructive Sleep Apnea Syndrome: Revealing Metabolic, Oxidative Stress and Immune-Related Pathways

There is strong evidence supporting the contribution of genetic factors to obstructive sleep apnea syndrome (OSAHS) susceptibility. In the current study we analyzed both in a clinical cohort and in silico, four single nucleotide polymorphisms SNPs, rs999944, rs75108997, rs35329661 and rs116133558 that have been associated with OSAHS. In 102 patients with OSAHS and 50 healthy volunteers, genetic testing of the above polymorphisms was performed. Polymorphism rs116133558 was invariant in our study population, whereas polymorphism rs35329661 was more than 95% invariant. Polymorphism rs999944 displayed significant (>5%) variance in our study population and was used in the binary logistic regression model. In silico analyses of the mechanism by which these three SNPs may affect the pathophysiology of OSAHS revealed a transcriptomic network of 274 genes. This network was involved in multiple cancer-associated gene signatures, as well as the adipogenesis pathway. This study, uncover a regulatory network in OSAHS using transcriptional targets of intergenic SNPs, and map their contributions in the pathophysiology of the syndrome on the interplay between adipocytokine signaling and cancer-related transcriptional dysregulation.