11 research outputs found
Profiling (adipo)cytokines in cancer cachexia
Get PDFCancer cachexia is an unmet clinical need that affects more than half of patients with cancer. Pro-inflammatory cytokines and adipokines could be involved in the pathogenesis and development of cachexia, but this relationship is not completely understood. This thesis aimed to examine and characterise the role of (adipo)cytokines in cancer cachexia.
A systematic review was conducted to evaluate the relationship between cytokines and cachexia in people with incurable cancer (Chapter 2). Interleukin-6 (IL-6) and tumour necrosis factor-α (TNF-α) were considerably elevated in cachectic individuals, and a high degree of methodological heterogeneity was observed. Furthermore, data from the REVOLUTION trial were analysed to determine if adiponectin, leptin, intelectin-1 and resistin can predict the modified Glasgow Prognostic Score (mGPS) and cachexia status (Chapter 3). Although adipokines could not predict any of the outcome variables in this study, leptin was negatively associated with mGPS and cachexia, while a positive relationship was identified between resistin and mGPS.
Previous research suggested that intelectin-1 might be involved in cancer cachexia. Given the limited availability of literature, a Bayesian meta-analysis was conducted to evaluate the role of intelectin-1 in cancer and its physiological concentration (Chapter 4). Intelectin-1 levels were substantially higher in patients with gastrointestinal cancer compared to controls. The meta-analysis also estimated that the physiological concentration of intelectin-1 ranges from 193ng/ml to 275ng/ml. Lastly, a cell culture model was designed to evaluate the effect of intelectin-1 on human myotubes (Chapter 5). Increased levels of intelectin-1 diminish insulin-mediated glucose uptake and downregulate the expression of genes involved in myogenesis.
To conclude, IL-6 and TNF-α were highly expressed in cancer cachexia. Leptin and resistin could also contribute to the development of this wasting syndrome, but to a lesser extent. Besides these (adipo)cytokines, intelectin-1 is another potential biomarker of cachexia and future research should focus on elucidating its mechanisms of action
The Emerging Role of Intelectin-1 in Cancer
Get PDFBackground: Intelectin (ITLN) is an adipokine with two homologs—ITLN1 and ITLN2—that has various physiological functions. Studies analyzing the relationship between ITLN and cancer are focused on ITLN1; the available literature on ITLN2 and cancer is limited. This review aims to evaluate the role of ITLN1 in cancer without imposing any inclusion criteria, to examine pro- and anticancer roles for ITLN1 and to discuss whether the relationship between ITLN and cancer is mediated by obesity. Findings: Overall, ITLN1 level was highly variable in cancer patients but different from healthy individuals. Compared with control groups, patients with gastrointestinal and prostate cancer showed increased concentrations of circulating ITLN1, while patients with gynecological, breast, bladder, and renal cancer had lower ITLN1 levels. Several studies also evaluated tissue and tumor expression of ITLN1. In gastrointestinal cancer, ITLN1 was increased in tumor tissue compared with adjacent healthy tissue and elevated in the visceral adipose tissue of patients compared with controls. Consequently, the high levels of circulating ITLN1 might be determined by the tumor and by the cancer-associated weight loss in gastrointestinal cancer. ITLN1 can activate the phosphoinositide-3-kinase-protein kinase B/Akt (PI3K/Akt) pathway. The improper regulation of this pathway may contribute to a series of cellular events that favor tumor development and progression. Obesity has been linked with an increased risk of developing some cancers. Indeed, low circulating ITLN1 levels may be a marker of the metabolic effects of obesity, rather than obesity per se, and might contribute to a deregulation of the PI3K/Akt pathway. Conclusions: ITLN1 could be associated with cancer formation and progression. Since circulating ITLN1 levels are highly variable and differ between cancer types, the local tumor production of ITLN1 could be more relevant in determining malignant behavior. Future research should aim to identify the source of ITLN1 variability, to understand the differences in ITLN1 between distinct tumor types, and to further explore the signaling pathways through which this adipokine influences cancer biology
A systematic review and Bayesian meta-analysis assessing intelectin-1 in cancer patients and healthy individuals
Get PDFBackground: Intelectin-1 (ITLN1) is an adipokine with multiple physiological functions, including a role in tumour formation and development. Previous research reported variable ITLN1 levels for cancer patients and healthy individuals. This study aimed to compare ITLN1 concentrations between controls and cancer patients and to determine the adipokine’s physiological level. Methods: Five databases were searched in January 2022 for studies that measured the level of ITLN1 in adults that were healthy or diagnosed with any type of cancer. After title, abstract and full-text screening, the methodological quality of the studies was assessed. The extracted data were meta-analysed using the R language and Bayesian statistical techniques. Results: Overall, 15 studies compared circulating ITLN1 levels between healthy individuals (n=3424) and cancer patients (n=1538), but no differences were observed between these studies. ITLN1 was not different between groups in an analysis that evaluated high-quality studies only (n=5). The meta-analysis indicated considerably higher ITLN1 levels in gastrointestinal (i.e., colorectal, pancreatic, gastric) cancer compared to controls, while the other cancer types did not demonstrate differences between groups. The mean ITLN1 level of healthy individuals was 234 ± 21ng/ml (n=136), while the average value in high-quality studies (n=52) was 257 ± 31ng/ml. Conclusion: Different types of cancer showed different circulating ITLN1 patterns. Circulating ITLN1 concentration was higher in gastrointestinal cancer compared to controls, with strong support from the meta-analytical model. Our analysis also determined the mean ITLN1 level in healthy individuals; this is a crucial starting point for understanding how this cytokine associates with diseases. Two-thirds of the studies were of low methodological quality and thus, future work in this field must focus on improved methods. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=303406, identifier CRD42022303406
The Emerging Role of Interleukin 1β (IL-1β) in Cancer Cachexia
Get PDFTreatment of cancer cachexia remains an unmet need. The host-tumour interface and the resulting sequestration of the pro-inflammatory cytokine Il-1β is critical in cachexia development. Neuroinflammation mediated via IL-1β through the hypothalamic pituitary axis results in increased muscle proteolysis and adipose lipolysis, thus creating a prolonged stress-like environment with loss of appetite and increased resting energy expenditure. Recent trials using a monoclonal antibody targeting IL-1β, canakinumab, have shown a potential role in lung cancer; however, a potential role of targeting IL-1β to treat cachexia in patients with lung cancer is unclear, yet the underlying pathophysiology provides a sound rationale that this may be a viable therapeutic approach
A systematic review examining the relationship between cytokines and cachexia in incurable cancer
Get PDFCancer cachexia is an unmet clinical need that affects more than 50% of patients with cancer. The systemic inflammatory response, which is mediated by a network of cytokines, has an established role in the genesis and maintenance of cancer as well as in cachexia; yet, the specific role of the cytokine milieu in cachexia requires elucidation. This systematic review aims to examine the relationship between cytokines and the cachexia syndrome in patients with incurable cancer. The databases MEDLINE, EMBASE, CINAHL, CENTRAL, PsycINFO, and Web of Science were searched for studies published between 01/01/2004 and 06/01/2020. Included studies measured cytokines and their relationship with cachexia and related symptoms/signs in adults with incurable cancer. After title screening (n = 5202), the abstracts (n = 1264) and the full-text studies (n = 322) were reviewed independently by two authors. The quality assessment of the selected papers was conducted using the modified Downs and Black checklist. Overall, 1277 patients with incurable cancer and 155 healthy controls were analysed in the 17 eligible studies. The mean age of the patients was 64 ± 15 (mean ± standard deviation). Only 34% of included participants were female. The included studies were assessed as moderate-quality to high-quality evidence (mean quality score: 7.8; range: 5–10). A total of 31 cytokines were examined in this review, of which interleukin-6 (IL-6, 14 studies) and tumour necrosis factor-α (TNF-α, 12 studies) were the most common. The definitions of cachexia and the weight-loss thresholds were highly variable across studies. Although the data could not be meta-analysed due to the high degree of methodological heterogeneity, the findings were discussed in a systematic manner. IL-6, TNF-α, and IL-8 were greater in cachectic patients compared with healthy individuals. Also, IL-6 levels were higher in cachectic participants as opposed to non-cachectic patients. Leptin, interferon-γ, IL-1β, IL-10, adiponectin, and ghrelin did not demonstrate any significant difference between groups when individuals with cancer cachexia were compared against non-cachectic patients or healthy participants. These findings suggest that a network of cytokines, commonly IL-6, TNF-α, and IL-8, are associated with the development of cachexia. Yet, this relationship is not proven to be causative and future studies should opt for longitudinal designs with consistent methodological approaches, as well as adequate techniques for analysing and reporting the results
A glossary for social-to-biological research
Get PDFResearch has shown that our socially structured experiences elicit a biological response, leading to the observation that numerous biomarkers (objective biological measures that are representative of various biological processes) are socially patterned. This ‘social-to-biological’ research is of interest to researchers across multiple disciplines and topics and especially to those with an interest in understanding the biological embodiment of the ‘social environment’. Combining social and biomarker data is also of relevance to those examining the biological determinants of social behaviours (for example, the relationship between genetics and certain behaviours like smoking). However, as much of the research involving biomarkers and social data are multidisciplinary, researchers need to understand why and how to optimally use and combine such data. This article provides a resource for researchers by introducing a range of commonly available biomarkers across studies and countries. Because of the breadth of possible analyses, we do not aim to provide an exhaustive and detailed review of each. Instead, we have structured the glossary to include: an easy-to-understand definition; a description of how it is measured; key considerations when using; and an example of its use in a relevant social-to-biological study. We have limited this glossary to biomarkers that are available in large health and social surveys or population-based cohort studies and focused on biomarkers in adults. We have structured the glossary around the main physiological systems studied in research on social to biological transition and those that go across systems and highlight some basic terms and key theoretical concepts
A glossary for social-to-biological research
Get PDFResearch has shown that our socially structured experiences elicit a biological response, leading to the observation that numerous biomarkers (objective biological measures that are representative of various biological processes) are socially patterned. This ‘social-to-biological’ research is of interest to researchers across multiple disciplines and topics and especially to those with an interest in understanding the biological embodiment of the ‘social environment’. Combining social and biomarker data is also of relevance to those examining the biological determinants of social behaviours (for example, the relationship between genetics and certain behaviours like smoking). However, as much of the research involving biomarkers and social data are multidisciplinary, researchers need to understand why and how to optimally use and combine such data. This article provides a resource for researchers by introducing a range of commonly available biomarkers across studies and countries. Because of the breadth of possible analyses, we do not aim to provide an exhaustive and detailed review of each. Instead, we have structured the glossary to include: an easy-to-understand definition; a description of how it is measured; key considerations when using; and an example of its use in a relevant social-to-biological study. We have limited this glossary to biomarkers that are available in large health and social surveys or population-based cohort studies and focused on biomarkers in adults. We have structured the glossary around the main physiological systems studied in research on social to biological transition and those that go across systems and highlight some basic terms and key theoretical concepts
May Measurement Month 2018: a pragmatic global screening campaign to raise awareness of blood pressure by the International Society of Hypertension
Get PDFAims
Raised blood pressure (BP) is the biggest contributor to mortality and disease burden worldwide and fewer than half of those with hypertension are aware of it. May Measurement Month (MMM) is a global campaign set up in 2017, to raise awareness of high BP and as a pragmatic solution to a lack of formal screening worldwide. The 2018 campaign was expanded, aiming to include more participants and countries.
Methods and results
Eighty-nine countries participated in MMM 2018. Volunteers (≥18 years) were recruited through opportunistic sampling at a variety of screening sites. Each participant had three BP measurements and completed a questionnaire on demographic, lifestyle, and environmental factors. Hypertension was defined as a systolic BP ≥140 mmHg or diastolic BP ≥90 mmHg, or taking antihypertensive medication. In total, 74.9% of screenees provided three BP readings. Multiple imputation using chained equations was used to impute missing readings. 1 504 963 individuals (mean age 45.3 years; 52.4% female) were screened. After multiple imputation, 502 079 (33.4%) individuals had hypertension, of whom 59.5% were aware of their diagnosis and 55.3% were taking antihypertensive medication. Of those on medication, 60.0% were controlled and of all hypertensives, 33.2% were controlled. We detected 224 285 individuals with untreated hypertension and 111 214 individuals with inadequately treated (systolic BP ≥ 140 mmHg or diastolic BP ≥ 90 mmHg) hypertension.
Conclusion
May Measurement Month expanded significantly compared with 2017, including more participants in more countries. The campaign identified over 335 000 adults with untreated or inadequately treated hypertension. In the absence of systematic screening programmes, MMM was effective at raising awareness at least among these individuals at risk
Influence of resistance training load on measures of skeletal muscle hypertrophy and improvements in maximal strength and neuromuscular task performance: A systematic review and meta-analysis
No full textThis systematic review and meta-analysis determined resistance training (RT) load effects on various muscle hypertrophy, strength, and neuromuscular performance task [e.g., countermovement jump (CMJ)] outcomes. Relevent studies comparing higher-load [> 60% 1-repetition maximum (RM) or < 15-RM] and lower-load (≤ 60% 1-RM or ≥ 15-RM) RT were identified, with 45 studies (from 4713 total) included in the meta-analysis. Higher- and lower-load RT induced similar muscle hypertrophy at the whole-body (lean/fat-free mass; [ES (95% CI) = 0.05 (−0.20 to 0.29), P = 0.70]), whole-muscle [ES = 0.06 (−0.11 to 0.24), P = 0.47], and muscle fibre [ES = 0.29 (−0.09 to 0.66), P = 0.13] levels. Higher-load RT further improved 1-RM [ES = 0.34 (0.15 to 0.52), P = 0.0003] and isometric [ES = 0.41 (0.07 to 0.76), P = 0.02] strength. The superiority of higher-load RT on 1-RM strength was greater in younger [ES = 0.34 (0.12 to 0.55), P = 0.002] versus older [ES = 0.20 (−0.00 to 0.41), P = 0.05] participants. Higher- and lower-load RT therefore induce similar muscle hypertrophy (at multiple physiological levels), while higher-load RT elicits superior 1-RM and isometric strength. The influence of RT loads on neuromuscular task performance is however unclear
DataSheet_1_A systematic review and Bayesian meta-analysis assessing intelectin-1 in cancer patients and healthy individuals.docx
No full textBackgroundIntelectin-1 (ITLN1) is an adipokine with multiple physiological functions, including a role in tumour formation and development. Previous research reported variable ITLN1 levels for cancer patients and healthy individuals. This study aimed to compare ITLN1 concentrations between controls and cancer patients and to determine the adipokine’s physiological level.MethodsFive databases were searched in January 2022 for studies that measured the level of ITLN1 in adults that were healthy or diagnosed with any type of cancer. After title, abstract and full-text screening, the methodological quality of the studies was assessed. The extracted data were meta-analysed using the R language and Bayesian statistical techniques.ResultsOverall, 15 studies compared circulating ITLN1 levels between healthy individuals (n=3424) and cancer patients (n=1538), but no differences were observed between these studies. ITLN1 was not different between groups in an analysis that evaluated high-quality studies only (n=5). The meta-analysis indicated considerably higher ITLN1 levels in gastrointestinal (i.e., colorectal, pancreatic, gastric) cancer compared to controls, while the other cancer types did not demonstrate differences between groups. The mean ITLN1 level of healthy individuals was 234 ± 21ng/ml (n=136), while the average value in high-quality studies (n=52) was 257 ± 31ng/ml.ConclusionDifferent types of cancer showed different circulating ITLN1 patterns. Circulating ITLN1 concentration was higher in gastrointestinal cancer compared to controls, with strong support from the meta-analytical model. Our analysis also determined the mean ITLN1 level in healthy individuals; this is a crucial starting point for understanding how this cytokine associates with diseases. Two-thirds of the studies were of low methodological quality and thus, future work in this field must focus on improved methods.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=303406, identifier CRD42022303406.</p
