Leptin's Immune Action: A Review Beyond Satiety

Mechanisms by which obesity regulates inflammation and anti-tumor immunity in cancer

Obesity is associated with an increased risk for 13 different cancers. The increased risk for cancer in obesity is mediated by obesity-associated changes in the immune system. Obesity has distinct effects on different types of inflammation that are tied to tumorigenesis. For example, obesity promotes chronic inflammation in adipose tissue that is tumor-promoting in peripheral tissues. Conversely, obesity inhibits acute inflammation that rejects tumors. Obesity therefore promotes cancer by differentially regulating chronic versus acute inflammation. Given that obesity is chronic, the initial inflammation in adipose tissue will lead to systemic inflammation that could induce compensatory anti-inflammatory reactions in peripheral tissues to suppress chronic inflammation. The overall effect of obesity in peripheral tissues is therefore dependent on the duration and severity of obesity. Adipose tissue is a complex tissue that is composed of many cell types in addition to adipocytes. Further, adipose tissue cellularity is different at different anatomical sites throughout the body. Consequently, the sensitivity of adipose tissue to obesity is dependent on the anatomical location of the adipose depot. For example, obesity induces more inflammation in visceral than subcutaneous adipose tissue. Based on these studies, the mechanisms by which obesity promotes tumorigenesis are multifactorial and immune cell type-specific. The objective of our paper is to discuss the cellular mechanisms by which obesity promotes tumorigenesis by regulating distinct types of inflammation in adipose tissue and the tumor microenvironment.

Is fat mass a better predictor of 6-month survival than muscle mass among African children aged 6-59 months with severe pneumonia?

BACKGROUND

Pneumonia remains the leading cause of mortality among children under 5 years. Poor nutritional status increases pneumonia mortality. Nutritional status assessed by anthropometry alone does not provide information on which body composition element predicts survival. Body composition proxy measures including arm-fat-area (AFA), arm-muscle-area (AMA), and arm-muscle-circumference (AMC) could be useful predictors.

OBJECTIVE

To compare the ability of fat and muscle mass indices to predict 6-month survival among children with severe pneumonia.

METHODS

This prospective cohort study was nested in the COAST-Nutrition trial (ISRCTN10829073, 06/06/2018) conducted between June 2020 and October 2022 in Uganda and Kenya. We included children aged 6-59 months hospitalized for severe pneumonia with hypoxemia. Children with severe malnutrition, known chronic lung or cardiac diseases were excluded. Anthropometry and clinical status were assessed at enrolment and at follow-up to day 180. We examined Receiver Operator Characteristic (ROC) curves of fat and muscle mass indices with 6-month survival as the outcome, and compared the areas under the curve (AUCs) using chi-square tests. Cox survival analysis models assessed time-to-mortality.

RESULTS

We included 369 participants. The median age was 15-months (IQR 9, 26), and 59.4% (219/369) of participants were male. The baseline measurements were: median MUAC 15.0 cm (IQR 14.0,16.0); arm-fat-area 5.6cm2 (IQR 4.7, 6.8); arm-muscle-area 11.4cm2 (IQR 10.0, 12.7); and arm-muscle-circumference 12.2 cm (IQR 11.5, 12.9). Sixteen (4.3%) participants died and 4 (1.1%) were lost-to-follow-up. The AUC for Arm-Fat-Area was not significantly higher than that for Arm-Muscle-Area and Arm-Muscle-Circumference [AUC 0.77 (95%CI 0.64-0.90) vs. 0.61 (95%CI 0.48-0.74), p = 0.09 and 0.63 (95%CI 0.51-0.75), p = 0.16 respectively], but was not statistically different from MUAC (AUC 0.73 (95%CI 0.62-0.85), p = 0.47). Increase in Arm-Fat-Area and Arm-Muscle-Circumference significantly improved survival [aHR 0.40 (95%CI 0.24-0.64), p = < 0.01 and 0.59 (95%CI 0.36-1.06), p = 0.03 respectively]. Survival prediction using Arm-Fat-Area was not statistically different from that of MUAC (p = 0.54).

CONCLUSIONS

Muscle mass did not predict 6-month survival better than fat mass in children with severe pneumonia. Fat mass appears to be a better predictor. Effects of fat and muscle could be considered for prognosis and targeted interventions.

Plasma proteomic profiling of bacterial cold water disease-resistant and -susceptible rainbow trout lines and biomarker discovery

Genetic variation for disease resistance is present in salmonid fish; however, the molecular basis is poorly understood, and biomarkers of disease susceptibility/resistance are unavailable. Previously, we selected a line of rainbow trout for high survival following standardized challenge with Flavobacterium psychrophilum (Fp), the causative agent of bacterial cold water disease. The resistant line (ARS-Fp-R) exhibits over 60 percentage points higher survival compared to a reference susceptible line (ARS-Fp-S). To gain insight into the differential host response between genetic lines, we compared the plasma proteomes from day 6 after intramuscular challenge. Pooled plasma from unhandled, PBS-injected, and Fp-injected groups were simultaneously analyzed using a TMT 6-plex label, and the relative abundance of 513 proteins was determined. Data are available via ProteomeXchange, with identifier PXD041308, and the relative protein abundance values were compared to mRNA measured from a prior, whole-body RNA-seq dataset. Our results identified a subset of differentially abundant intracellular proteins was identified, including troponin and myosin, which were not transcriptionally regulated, suggesting that these proteins were released into plasma following pathogen-induced tissue damage. A separate subset of high-abundance, secreted proteins were transcriptionally regulated in infected fish. The highest differentially expressed protein was a C1q family member (designated complement C1q-like protein 3; C1q-LP3) that was upregulated over 20-fold in the infected susceptible line while only modestly upregulated, 1.8-fold, in the infected resistant line. Validation of biomarkers was performed using immunoassays and C1q-LP3, skeletal muscle troponin C, cathelcidin 2, haptoglobin, leptin, and growth and differentiation factor 15 exhibited elevated concentration in susceptible line plasma. Complement factor H-like 1 exhibited higher abundance in the resistant line compared to the susceptible line in both control and challenged fish and thus was a baseline differentiator between lines. C1q-LP3 and STNC were elevated in Atlantic salmon plasma following experimental challenge with Fp. In summary, these findings further the understanding of the differential host response to Fp and identifies salmonid biomarkers that may have use for genetic line evaluation and on-farm health monitoring.

Malnutrition and Erythropoietin Resistance among Patients with End-Stage Kidney Disease: Where Is the Perpetrator of Disaster?

BACKGROUND

Hemodialyzed patients with poor erythropoietin response tend to have low volume of visceral adipose tissue and score high on malnutrition-inflammation score. This study investigates in-depth the role of leptin and chosen cytokines in the development of malnutrition-inflammation syndrome (MIS) and erythropoietin resistance.

METHODS

Eighty-one hemodialyzed patients with erythropoietin-treated anemia were enrolled in the study. Their body composition was measured. Erythropoietin resistance index was calculated. Blood samples for leptin, IL-6, IL-18, TNF-alpha, and IL-1-alpha serum levels were drawn.

RESULTS

Leptin showed negative correlation with erythropoietin resistance index (ERI), whilst IL-6 showed the opposite. IL-6 seemed to be linked more to HD parameters and vintage, while TNF-alpha and leptin were more dependent on body composition. IL-18 and IL-1-alpha did not affect nutritional parameters nor ERI.

CONCLUSION

Modulation of adipokine- and cytokine-related signaling is a promising target in tempering malnutrition in hemodialyzed, and thus achieving better outcomes in anemia treatment. Large clinical studies that target the inflammatory response in hemodialysis, especially regarding IL-6, TNF-alpha, and leptin, would be of great worth.