Levels of Adiponectin Expression in Peri-Renal and Subcutaneous Adipose Tissue and Its Determinants in Human Biopsied Samples

The role of perirenal adipose tissue deposition in chronic kidney disease progression: Mechanisms and therapeutic implications

Chronic kidney disease (CKD) represents a significant and escalating global health challenge, with morbidity and mortality rates rising steadily. Evidence increasingly implicates perirenal adipose tissue (PRAT) deposition as a contributing factor in the pathogenesis of CKD. This review explores how PRAT deposition may exert deleterious effects on renal structure and function. The anatomical proximity of PRAT to the kidneys not only potentially causes mechanical compression but also leads to the dysregulated secretion of adipokines and inflammatory mediators, such as adiponectin, leptin, visfatin, tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and exosomes. Additionally, PRAT deposition may contribute to renal lipotoxicity through elevated levels of free fatty acids (FFA), triglycerides (TAG), diacylglycerol (DAG), and ceramides (Cer). PRAT deposition is also linked to the hyperactivation of the renin-angiotensin-aldosterone system (RAAS), which further exacerbates CKD progression. Recognizing PRAT deposition as an independent risk factor for CKD underscores the potential of targeting PRAT as a novel strategy for the prevention and management of CKD. This review further discusses interventions that could include measuring PRAT thickness to establish a baseline, managing metabolic risk factors that promote its deposition, and inhibiting key PRAT-induced signaling pathways.

Role of perirenal adiposity in renal dysfunction among CKD individuals with or without diabetes: a Japanese cross-sectional study

INTRODUCTION

It remains unclear whether increased perirenal fat (PRF) accumulation is equally related to renal involvement in patients with and without diabetes mellitus (DM). We evaluated the association between PRF volume (PRFV) and low glomerular filtration rate (GFR) and proteinuria in people with or without type 2 diabetes mellitus (T2DM).

RESEARCH DESIGN AND METHODS

We performed a cross-sectional analysis of 473 individuals without T2DM (non-DM, n=202) and with T2DM (DM, n=271). PRFV (cm3), obtained from non-contrast CT, was indexed as PRF index (PRFV/body surface area, cm3/m2). Multivariate-adjusted models were used to determine the ORs of PRFV and PRFV index for detecting estimated GFR (eGFR) decrease of <60 mL/min/1.73 m2 proteinuria onset, or both.

RESULTS

Although body mass index (BMI), visceral fat area, and waist circumference were comparable between the non-DM and DM groups, kidney volume, PRFV, and PRFV index were higher in individuals with T2DM than in those without T2DM. In the multivariate analysis, after adjusting for age, sex, BMI, hypertension, smoking history, and visceral fat area ≥100 cm2, the cut-off values of PRFV index were associated with an eGFR<60 in individuals with DM (OR 6.01, 95% CI 2.20 to 16.4, p<0.001) but not in those without DM.

CONCLUSIONS

PRFV is associated with low eGFR in patients with T2DM but not in those without T2DM. This suggests that PRF accumulation is more closely related to the onset and progression of diabetic kidney disease (DKD) than non-DKD. Clarifying the mechanisms through which PRF influences DKD development could pave the way for novel prevention and treatment strategies.

The association between obesity indicators and metabolic risk factors in type-2 diabetic patients

Rationale and objectives

Obesity, accumulation of adipose tissue, is a global disease that can lead to cardiovascular and metabolic complications. The aim of this study was to investigate the relationship between obesity indicators and metabolic risk factors in type 2 diabetes mellitus (T2DM) patients.

Materials and methods

A total of 337 T2DM subjects were included in our study. The metabolic risk factors including diabetes duration, fast plasma glucose (FPG), height, weight, systolic blood pressure (SBP), diastolic blood pressure (DBP), estimated average glucose (eAG), glycated hemoglobin (HbA1c), total cholesterol (TC), high-density lipoprotein-cholesterol (HDL-c), low-density lipoprotein-cholesterol (LDL-c), triglyceride (TG), blood urea nitrogen (BUN), serum creatinine (Scr), free fatty acid (FFA), uric acid (UA), cystatin c (cysc), albumin (Alb), urinary albumin creatinine ratio (UACR) were recorded. The obesity indicators included body surface area (BSA), body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), para-perirenal fat thickness (PRFT), total abdominal fat (TAF), subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT). The association between obesity indicators and metabolic risk factors was investigated by univariate and multivariate analysis.

Results

HDL-c was independently associated with WHR and PRFT (β = -0.126 vs. -0.214, both p < 0.05). TG and Scr were both independently associated with PRFT (β = 0.173 vs. 0.218, both p < 0.01, respectively). UA was independently associated with BSA (β = 0.172, p < 0.01) and PRFT (β = 0.151, p < 0.01). cysc, Alb and UACR were independently associated with WC (β = 0.274 vs. 0.204 vs. 0.182, all p < 0.01).

Conclusion

In T2DM patients, obesity indicators were significantly associated with metabolic risk factors.

Sexual Dimorphism in Cardiovascular Biomarkers: Clinical and Research Implications

Sex-based differences in cardiovascular disease presentation, diagnosis, and response to therapies are well established, but mechanistic understanding and translation to clinical applications are limited. Blood-based biomarkers have become an important tool for interrogating biologic pathways. Understanding sexual dimorphism in the relationship between biomarkers and cardiovascular disease will enhance our insights into cardiovascular disease pathogenesis in women, with potential to translate to improved individualized care for men and women with or at risk for cardiovascular disease. In this review, we examine how biologic sex associates with differential levels of blood-based biomarkers and influences the effect of biomarkers on disease outcomes. We further summarize key differences in blood-based cardiovascular biomarkers along central biologic pathways, including myocardial stretch/injury, inflammation, adipose tissue metabolism, and fibrosis pathways in men versus women. Finally, we present recommendations for leveraging our current knowledge of sex differences in blood-based biomarkers for future research and clinical innovation.

Perirenal Fat Volume Is Positively Associated With Serum Uric Acid Levels in Chinese Adults

BACKGROUND

Visceral fat has been considered an important risk factor of elevated serum uric acid (SUA). Perirenal fat is a unique visceral fat around the kidneys that has special morphological and physiological features while its relationship with SUA remains incompletely elucidated. This study aimed to assess the association between perirenal fat volume (PrFV) and SUA.

METHODS

A cross-sectional study was conducted in 102 subjects aged ≥ 18 years old recruited from Nanjing,China. The clinical characteristics including age, sex, drinking behavior, history of hypertension, body mass index, waist circumference, total cholesterol, fast plasma glucose, urea, serum creatinine, C-reactive protein, and SUA were recorded. PrFV was measured by ultrasonography. Multivariate linear models and the restricted cubic spline were used to investigate the association between PrFV and SUA.

RESULTS

The median age of this study population was 52.5 (42.0-60.0) years and 56.9% were female. The median value of SUA was 5.73 mg/dL (4.58-6.80 mg/dL). The subjects were divided by PrFV tertiles and we found that the subjects in the highest PrFV tertile had a higher level of SUA compared to those in the lowest tertile (β=1.86, 95%CI 1.23-2.48, P for trend <0.001).The positive association also remained after adjustment for potential covariates (tertile3 versus tertile1: β=0.99, 95%CI 0.35-1.63, P for trend =0.005). There was an increase of approximately 0.53 mg/dL in SUA per 1-fold increase in PrFV (β=0.53, 95%CI 0.02-1.04, P for nonlinearity = 0.637).

CONCLUSION

Our results confirmed a positive independent relationship between PrFV and SUA in Chinese adults. This study suggested that perirenal fat might constitute a potential risk factor for elevated serum uric acid levels.

Novel strategies for glycaemic control and preventing diabetic complications applying the clustering-based classification of adult-onset diabetes mellitus: A perspective

Diabetes mellitus results from an interplay between insulin resistance and β-cell dysfunction. Since their relative contributions to its pathogenesis are difficult to quantify, therapeutic strategies for glycaemic control are determined primarily based on two limited metrics: plasma glucose and haemoglobin A1c. Recent attempts have been made to subclassify diabetes mellitus to better predict its associated pathology and plan appropriate therapeutic strategies. These classifications are based on data-driven cluster analysis using autoimmunity, age, obesity (metabolically unhealthy and healthy phenotypes), insulin secretory capacity and resistance, and ethnicity. This review addresses potential therapeutic strategies for the cluster-based classifications of adult-onset diabetes mellitus to achieve better glycaemic control and prevent or at least delay the concomitant complications.

Usefulness of the mayo adhesive probability score as a predictive factor for renal function deterioration after partial nephrectomy: a retrospective case-control study

PURPOSE

Whether the Mayo adhesive probability score, an index of the perinephric fat environment, could be a predictive factor for renal function deterioration after partial nephrectomy was investigated.

METHODS

A retrospective case-control study of 78 patients who underwent laparoscopic partial nephrectomy was performed. An estimated glomerular filtration rate preservation rate at ≤ 90% at 3 months after surgery was defined as postoperative renal function deterioration. These patients were divided into two groups (non-deterioration and deterioration groups). Patient factors including Mayo adhesive probability scores (both tumor and unaffected sides) and surgical factors were evaluated to identify the predictors for postoperative renal function deterioration. The statistical analysis used univariate and multivariate logistic regression analyses.

RESULTS

Thirty-seven (47.4%) patients had postoperative renal function deterioration after partial nephrectomy. Univariate analysis identified Mayo adhesive probability score on the unaffected side (p = 0.02), and warm ischemia time (p < 0.01) as predictors of postoperative renal function deterioration. On multivariate analyses, Mayo adhesive probability score on the unaffected side (odds ratio: 1.38 [1.05-1.79], p = 0.02) and warm ischemia time (odds ratio: 1.04 [1.01-1.07], p < 0.01) were significantly associated with postoperative renal function deterioration as same as univariate analysis. On receive operating characteristic curve analysis, Mayo adhesive probability score on the unaffected side (cutoff value 1.5; p = 0.02) and warm ischemia time (cutoff value 26.5 min; p = 0.01) were significant predictors of renal function deterioration 3 month after surgery.

CONCLUSION

The Mayo adhesive probability score on the unaffected side and warm ischemia time are useful predictors for renal function deterioration after partial nephrectomy.

TRIAL REGISTRATION NUMBER

2019-249, January 21st, 2019, retrospectively registered.

Cardiorenal Fat: A Cardiovascular Risk Factor With Implications in Chronic Kidney Disease

There is a growing interest in the potential role of adipose tissues in cardiac and renal pathophysiology, and determining the mechanisms by which fat compartments around the heart and kidneys influence cardiovascular disease is of clinical importance in both general and high-risk populations. Epicardial fat and perirenal fat have been associated with adverse outcomes in chronic kidney disease (CKD) patients. Epicardial fat is a rich source of free fatty acids and is capable of secreting inflammatory and pro-atherogenic cytokines that promote atherosclerosis through a local paracrine effect. Recent evidence has demonstrated that perirenal fat has a closer correlation with kidney diseases than other visceral fat deposits in obesity or metabolic disturbances. Moreover, perirenal fat has been reported as an independent risk factor for CKD progression and even associated with cardiorenal dysfunction. Accordingly, these forms of organ-specific fat deposits may act as a connecter between vascular and cardiorenal disease. This review explores the possible links between epicardial and perirenal fat and its significant role as a modulator of cardiorenal dysfunction in CKD patients.

Obesity, malnutrition, and trace element deficiency in the coronavirus disease (COVID-19) pandemic: An overview

The world is currently facing the coronavirus disease (COVID-19) pandemic which places great pressure on health care systems and workers, often presents with severe clinical features, and sometimes requires admission into intensive care units. Derangements in nutritional status, both for obesity and malnutrition, are relevant for the clinical outcome in acute illness. Systemic inflammation, immune system impairment, sarcopenia, and preexisting associated conditions, such as respiratory, cardiovascular, and metabolic diseases related to obesity, could act as crucial factors linking nutritional status and the course and outcome of COVID-19. Nevertheless, vitamins and trace elements play an essential role in modulating immune response and inflammatory status. Overall, evaluation of the patient's nutritional status is not negligible for its implications on susceptibility, course, severity, and responsiveness to therapies, in order to perform a tailored nutritional intervention as an integral part of the treatment of patients with COVID-19. The aim of this study was to review the current data on the relevance of nutritional status, including trace elements and vitamin status, in influencing the course and outcome of the disease 3 mo after the World Health Organization's declaration of COVID-19 as a pandemic.