Serum resistin as an independent marker of aortic stiffness in patients with coronary artery disease

Resistin: A Potential Indicator of Aortic Stiffness in Non-Dialysis Chronic Kidney Disease Patients

Background and Objectives: In the progression and development of atherosclerosis, resistin plays a significant role. Chronic kidney disease (CKD), frequently associated with atherosclerosis, exhibits a marked increase in morbidity and mortality rates. This study set out to explore the association between aortic stiffness and serum levels of resistin in non-dialysis-dependent CKD patients ranging from stages 3 to 5. Materials and Methods: We collected fasting blood samples from 240 CKD patients across stages 3 to 5. The concentration of resistin in serum was determined using a commercially available enzyme immunoassay kit. Those patients who exhibited a carotid-femoral pulse wave velocity (cfPWV) greater than 10 m/s were identified as the aortic stiffness group. Results: Out of the 240 CKD patients, 88 (36.7%) were classified within the aortic stiffness group. This group demonstrated higher incidences of diabetes, advanced age, increased body weight, body mass index, body fat mass, systolic and diastolic blood pressure, fasting glucose, and serum resistin levels. Multivariate logistic regression analysis highlighted resistin, diabetes, and body weight as independent predictors of aortic stiffness. Additionally, body fat mass, logarithmically transformed cfPWV (log-cfPWV) values and log-triglyceride levels were independent predictors of log-resistin levels by multivariate stepwise linear regression analysis. Conclusions: In CKD patients from stages 3 to 5, a positive correlation exists between elevated serum resistin levels and cfPWV values, identifying resistin as a potential predictor of aortic stiffness.

The Association between Serum Resistin Level, Resistin (-420C/G) Single Nucleotide Variant, and Markers of Endothelial Dysfunction, including Salt Taste Preference in Hypertensive Patients

Background: Resistin action links to conditions such as diabetes, obesity, but its role in hypertension is less well understood. This study aimed to estimate the relationship between resistin (−420G/C) single nucleotide variant (SNV) and markers associated with endothelial dysfunction in hypertension. Methods: The study enrolled 162 hypertensive patients (HT) and 165 non-hypertensive (NHT) patients. Resistin serum concentration was estimated with immuoenzymatic assay. Anthropometric measurements, blood pressure and arterial stiffness index (SI), uric acid (UA) serum concentration, and salty taste preference of normal (NS) or high (HS) were assessed in the study. Genotyping was achieved by polymerase chain reaction-restriction fragment length polymorphism. Results: Resistin concentration and SI do not differ significantly between HT and NHT individuals; UA significantly increased in HT subjects. Resistin, UA, and SI did not differ among particular resistin genotypes in HT, NHT, NS, or HS groups. GG and CG genotypes were more frequent (OR 1.57 (95% CI; 1.01–2.43); p = 0.04) in hypertensive individuals than the NHT group, but less frequent (OR 0.58 (95% CI; 0.37–0.91); p = 0.01) in HS patients compared to NS individuals. Concerning HT patients with different salt preferences, GG + CG genotypes were less frequent (OR 0.50 (95% CI; 0.26–0.97); p = 0.04) in the HS group than in NS individuals. HT carriers of GG and CG genotype have significantly increased UA concentrations compared to the respective NHT subjects. HS individuals carrying GG and CG genotypes have higher SI values than the NS group. Allele G of SNV (−420G/C) adjusted for age, BMI, serum resistin, UA concentration, salt taste preference, SI, and HR values increased the risk of developing hypertensive phenotype 1.8 fold. Conclusions: Resistin SNV (−420G/C) is related to several markers associated with endothelial dysfunction, including salt taste preference in hypertensive patients.

Resistin and Cardiovascular Disease: A Review of the Current Literature Regarding Clinical and Pathological Relationships

Serum resistin, mainly secreted by the bone marrow, monocytes, and macrophages, contributes to many processes, including endothelial dysfunction, Vascular Smooth Muscle Cell (VSMC) proliferation, and atherothrombosis demonstrating effects on the development of hypertension and Coronary Artery Disease (CAD). Previously published clinical studies have shown that plasma resistin levels are significantly associated with cardiovascular disease risk factors and adverse clinical outcomes associated with the condition. Resistin is associated with vascular smooth muscle cell dysfunction in vitro, most plausibly due to its relationship with oxidative stress in advanced atherosclerosis whereas in vivo studies have shown resistin to be associated with intimal hyperplasia. We aimed to summarize the role of resistin on cardiovascular disease (CVD), as we could not find any review focused on the role of resistin on CVD.

Aortic Stiffness: Epidemiology, Risk Factors, and Relevant Biomarkers

Aortic stiffness (AoS) is a maladaptive response to hemodynamic stress and both modifiable and non-modifiable risk factors, and elevated AoS increases afterload for the heart. AoS is a non-invasive marker of cardiovascular health and metabolic dysfunction. Implementing AoS as a diagnostic tool is challenging as it increases with age and varies amongst races. AoS is associated with lifestyle factors such as alcohol and smoking, as well as hypertension and comorbid conditions including metabolic syndrome and its components. Multiple studies have investigated various biomarkers associated with increased AoS, and this area is of particular interest given that these markers can highlight pathophysiologic pathways and specific therapeutic targets in the future. These biomarkers include those involved in the inflammatory cascade, anti-aging genes, and the renin-angiotensin aldosterone system. In the future, targeting AoS rather than blood pressure itself may be the key to improving vascular health and outcomes. In this review, we will discuss the current understanding of AoS, measurement of AoS and the challenges in interpretation, associated biomarkers, and possible therapeutic avenues for modulation of AoS.

Adipokines and Arterial Stiffness in Obesity

Adipokines are active molecules with pleiotropic effects produced by adipose tissue and involved in obesity-related metabolic and cardiovascular diseases. Arterial stiffness, which is a consequence of arteriosclerosis, has been shown to be an independent predictor of cardiovascular morbidity and mortality. The pathogenesis of arterial stiffness is complex but incompletely understood. Adipokines dysregulation may induce, by various mechanisms, vascular inflammation, endothelial dysfunction, and vascular remodeling, leading to increased arterial stiffness. This article summarizes literature data regarding adipokine-related pathogenetic mechanisms involved in the development of arterial stiffness, particularly in obesity, as well as the results of clinical and epidemiological studies which investigated the relationship between adipokines and arterial stiffness.

Resistin in metabolism, inflammation, and disease

Resistin is a small secretory protein that has a pleiotropic role in rodents and humans. Both rodent resistin and human resistin have an extremely stable and high-order multimeric structure. Moreover, there is significant variation in the source of secretion and the diversity of functions of resistin. Mouse resistin resists insulin action and contributes to type 2 diabetes mellitus, while human resistin plays a role in inflammation and also functions as a small accessory chaperone. Currently, active research in the area identified a significant role for resistin in stress biology and as a biomarker in diagnostics to evaluate disease status and treatment outcome. This review summarizes recent developments within resistin biology including their association with obesity, inflammation, stress response mechanisms, and its role in clinical diagnostics.

Correlation between sclerostin and Dickkopf-1 with aortic arterial stiffness in patients with type 2 diabetes: A prospective, cross-sectional study

BACKGROUND

Sclerostin and Dickkopf-1 are extracellular inhibitors of the canonical Wnt/β-catenin signalling pathway, which is implicated in the development of arterial stiffness. However, the correlation between aortic stiffness and sclerostin or Dickkopf-1 levels in patients with type 2 diabetes mellitus is unknown.

METHODS

Fasting blood samples were collected from 125 patients with type 2 diabetes mellitus. Aortic stiffness was measured by carotid-femoral pulse wave velocity, and high aortic stiffness was defined by a carotid-femoral pulse wave velocity of >10 m/s. The serum sclerostin and Dickkopf-1 concentrations were determined using commercially available enzyme-linked immunosorbent assays.

RESULTS

In total, 46 patients with type 2 diabetes mellitus (36.8%) had high levels of aortic stiffness. Compared to the control group without aortic stiffness, this group was significantly older, had higher systolic and diastolic blood pressures, had higher blood urea nitrogen, creatinine, urinary albumin-to-creatinine ratio and serum sclerostin levels, and had significantly lower high-density lipoprotein cholesterol levels and estimated glomerular filtration rates. After adjusting for confounders, serum sclerostin [odds ratio = 1.005 (1.002-1.007), p = 0.002] levels remained an independent predictor of aortic stiffness. Multivariate analysis showed that the serum sclerostin level ( β = 0.374, adjusted R² change = 0.221, p < 0.001) was positively associated with carotid-femoral pulse wave velocity.

CONCLUSION

Serum levels of sclerostin, but not Dickkopf-1, are positively correlated with carotid-femoral pulse wave velocity and independently predict aortic stiffness in patients with type 2 diabetes mellitus.

Metabolic Syndrome With Aortic Arterial Stiffness And First Hospitalization Or Mortality In Coronary Artery Disease Patients

PURPOSE

Metabolic syndrome (MetS) and aortic arterial stiffness (AS) are risk factors for future cardiovascular events. We evaluated their roles in first hospitalization or all-cause mortality prediction in coronary artery disease (CAD) patients.

PATIENTS AND METHODS

From January to December 2012, 115 CAD patients were enrolled from a single center and followed up for 5.5 years. The composite endpoint included hospitalization for unstable angina, myocardial infarction, revascularization, or heart failure and all-cause mortality. Patients with carotid-femoral pulse wave velocity > 10 m/s (measured using applanation tonometry) constituted the high AS group.

RESULTS

During a median 54-month follow-up, there were 43 (37.4%) and 11 (9.6%) hospitalization and mortality events, respectively. Overall, 41 (35.7%) and 70 (60.9%) patients were diagnosed with AS and MetS, respectively. CAD patients with high AS had higher diabetes and MetS percentages, were older, and had higher waist circumference and systolic blood pressure (SBP) but lower glomerular filtration rate than those with low AS. Multivariate logistic regression analysis revealed old age (P < 0.001), diabetes (P = 0.003), and high waist circumference (P = 0.044) and SBP (P = 0.007) as independent predictors of AS in CAD patients. Kaplan-Meier analysis showed that CAD patients with concurrent MetS and high AS had a higher risk for hospitalization (log rank test, P = 0.005) or developing all-cause mortality (log rank test, P = 0.002). Compared with CAD patients without MetS or AS, composite outcome development risk in those with both the conditions was 10.2-fold higher (P < 0.001); this risk was 6.54-fold higher in those with AS alone (P = 0.007).

CONCLUSION

In CAD patients, age, diabetes, and high waist circumference and SBP are the independent predictors of AS. Additionally, CAD patients with AS with and without MetS have a high first hospitalization or all-cause mortality development risk.

Serum levels of sclerostin as a potential biomarker in central arterial stiffness among hypertensive patients

BACKGROUND

Sclerostin is known to be a canonical Wnt/β-catenin signaling pathway inhibitor, while the Wnt/β-catenin signaling pathway is proposed to be involved in the development of arterial stiffness. This study aims to investigate the relationship between serum sclerostin levels and carotid-femoral pulse wave velocity (cfPWV) among hypertensive patients.

METHODS

Fasting blood samples were obtained from 105 hypertensive patients. Patients with cfPWV values of > 10 m/s were classified in the high arterial stiffness group, whereas those with cfPWV values of ≤10 m/s were assigned to the low arterial stiffness group. Serum sclerostin and Dickkopf-1 (DKK1) levels were quantified using commercially available enzyme-linked immunosorbent assays.

RESULTS

Thirty-six hypertensive patients (34.3%) who belonged to the high arterial stiffness group were generally older (p < 0.001), presented with lower estimated glomerular filtration rates (eGFR, p = 0.014), higher incidence of diabetes mellitus (p = 0.030), average systolic blood pressures (SBP, p = 0.013), pulse pressure (p = 0.026), serum creatinine levels (p = 0.013), intact parathyroid hormone levels (iPTH, p = 0.003), and sclerostin levels (p < 0.001) than their counterparts in the low arterial stiffness group. A multivariable logistic regression analysis identified sclerostin as an independent predictor of arterial stiffness in hypertensive patients (odds ratio, 1.042; 95% confidence interval (CI), 1.017-1.068; p = 0.001). Multivariable forward stepwise linear regression analysis also showed that serum sclerostin level (β = 0.255, adjusted R2 change: 0.146, p = 0.003) was positively associated with cfPWV values in patients with hypertension.

CONCLUSIONS

In this study, serum sclerostin level, but not DKK1, is found to be positively correlated with cfPWV values and is identified as an independent predictor of arterial stiffness in hypertensive patients after adjusting for significant confounders.

Towards frailty biomarkers: Candidates from genes and pathways regulated in aging and age-related diseases

OBJECTIVE

Use of the frailty index to measure an accumulation of deficits has been proven a valuable method for identifying elderly people at risk for increased vulnerability, disease, injury, and mortality. However, complementary molecular frailty biomarkers or ideally biomarker panels have not yet been identified. We conducted a systematic search to identify biomarker candidates for a frailty biomarker panel.

METHODS

Gene expression databases were searched (http://genomics.senescence.info/genes including GenAge, AnAge, LongevityMap, CellAge, DrugAge, Digital Aging Atlas) to identify genes regulated in aging, longevity, and age-related diseases with a focus on secreted factors or molecules detectable in body fluids as potential frailty biomarkers. Factors broadly expressed, related to several "hallmark of aging" pathways as well as used or predicted as biomarkers in other disease settings, particularly age-related pathologies, were identified. This set of biomarkers was further expanded according to the expertise and experience of the authors. In the next step, biomarkers were assigned to six "hallmark of aging" pathways, namely (1) inflammation, (2) mitochondria and apoptosis, (3) calcium homeostasis, (4) fibrosis, (5) NMJ (neuromuscular junction) and neurons, (6) cytoskeleton and hormones, or (7) other principles and an extensive literature search was performed for each candidate to explore their potential and priority as frailty biomarkers.

RESULTS

A total of 44 markers were evaluated in the seven categories listed above, and 19 were awarded a high priority score, 22 identified as medium priority and three were low priority. In each category high and medium priority markers were identified.

CONCLUSION

Biomarker panels for frailty would be of high value and better than single markers. Based on our search we would propose a core panel of frailty biomarkers consisting of (1) CXCL10 (C-X-C motif chemokine ligand 10), IL-6 (interleukin 6), CX3CL1 (C-X3-C motif chemokine ligand 1), (2) GDF15 (growth differentiation factor 15), FNDC5 (fibronectin type III domain containing 5), vimentin (VIM), (3) regucalcin (RGN/SMP30), calreticulin, (4) PLAU (plasminogen activator, urokinase), AGT (angiotensinogen), (5) BDNF (brain derived neurotrophic factor), progranulin (PGRN), (6) α-klotho (KL), FGF23 (fibroblast growth factor 23), FGF21, leptin (LEP), (7) miRNA (micro Ribonucleic acid) panel (to be further defined), AHCY (adenosylhomocysteinase) and KRT18 (keratin 18). An expanded panel would also include (1) pentraxin (PTX3), sVCAM/ICAM (soluble vascular cell adhesion molecule 1/Intercellular adhesion molecule 1), defensin α, (2) APP (amyloid beta precursor protein), LDH (lactate dehydrogenase), (3) S100B (S100 calcium binding protein B), (4) TGFβ (transforming growth factor beta), PAI-1 (plasminogen activator inhibitor 1), TGM2 (transglutaminase 2), (5) sRAGE (soluble receptor for advanced glycosylation end products), HMGB1 (high mobility group box 1), C3/C1Q (complement factor 3/1Q), ST2 (Interleukin 1 receptor like 1), agrin (AGRN), (6) IGF-1 (insulin-like growth factor 1), resistin (RETN), adiponectin (ADIPOQ), ghrelin (GHRL), growth hormone (GH), (7) microparticle panel (to be further defined), GpnmB (glycoprotein nonmetastatic melanoma protein B) and lactoferrin (LTF). We believe that these predicted panels need to be experimentally explored in animal models and frail cohorts in order to ascertain their diagnostic, prognostic and therapeutic potential.

Serum resistin is associated with impaired endothelial function and a higher rate of adverse cardiac events in patients with peripheral artery disease

OBJECTIVE

Resistin is a hormone that has been associated with metabolic syndrome and cardiovascular disease. The role of resistin in patients with peripheral artery disease (PAD) has not been fully explored. This study seeks to understand the relationship between serum resistin, vascular function, and cardiovascular outcomes in patients with PAD.

METHODS

There were 106 patients with PAD who were recruited between 2011 and 2016. Patients attended a baseline visit during which a comprehensive vascular physiology assessment including medical and surgical history, radial artery tonometry, and flow mediated-vasodilation (FMD) was completed. A blood sample was drawn, and serum resistin was assayed using enzyme-linked immunosorbent assay kits. Using the time of study enrollment as the time of origin, incident major adverse cardiac events (MACEs) were identified by subsequent chart review and defined as a composite end point of myocardial infarction, coronary revascularization, transient ischemic attack, stroke, or death from a cardiac cause.

RESULTS

Patients had a mean age of 68 ± 8 years, were largely white (75%), and had comorbidities commonly associated with PAD including hypertension (92%), hyperlipidemia (87%), coronary artery disease (37%), and diabetes mellitus (38%). After stratification by resistin quartile, higher resistin quartiles were significantly associated with an older age, a greater number of pack-years smoked, and a lower estimated glomerular filtration rate. Despite similar comorbidities and medication use, endothelial function, as measured by FMD, was significantly lower with increasing resistin quartile (I, 9.1% ± 3.3%; II, 7.1% ± 3.5%; III, 5.8% ± 4.0%; IV, 5.6% ± 3.5%; P = .002). In multivariable linear regression, higher resistin quartiles (III and IV) were associated with lower FMD relative to quartile I after adjusting for several patient characteristics, medications, and comorbidities (III, -2.26 [95% confidence interval (CI), -4.51 to -0.01; P = .05]; IV, -2.53 [95% CI, -4.87 to -0.20; P = .03]). During a median follow-up period of 36 months (interquartile range, 29-45 months), 21 patients experienced the primary end point. In a Cox proportional hazards model adjusted for smoking status, coronary artery disease, and age, each 1 ng/mL increase in resistin was associated with a 10% increased risk of MACEs (hazard ratio, 1.10; 95% CI, 1.00-1.20; P = .04).

CONCLUSIONS

In patients with PAD, higher levels of resistin were associated with impaired endothelial function and an increased rate of MACEs. These results suggest that resistin may be a marker or effector of impaired vascular physiology and adverse cardiac outcomes in patients with PAD. Further research is needed to determine the potential mechanisms by which resistin may impair endothelial function and increase MACEs in this population.

Association between hyperleptinemia and cardiovascular outcomes in patients with coronary artery disease

Purpose

Hyperleptinemia has been independently associated with human cardiovascular (CV) diseases. Accordingly, we evaluate the association between serum leptin and future CV events in patients with coronary artery disease (CAD).

Patients and methods

This study enrolled 98 patients with CAD from January to December 2012. The primary endpoint included incidences of major adverse CV events and hospitalization. Patients follow-up had been completed on June 30, 2017.

Results

After a median follow-up of 52 months, 43 CV events had occurred. Patients with CV events had higher systolic blood pressure (P = 0.030), total cholesterol (P = 0.034), C-reactive protein (P = 0.018), and serum leptin levels (P = 0.001) than those without CV events. Kaplan–Meier analysis showed greater cumulative incidences of CV events in the high leptin group (median leptin concentration >6.03 ng/mL) than in the low leptin group (log-rank P = 0.012). Multivariate Cox regression analysis showed that triglyceride (HR: 1.010; 95% CI: 1.001–1.018; P = 0.022) and leptin levels (HR: 1.054; 95% CI: 1.026–1.082; P < 0.001) were independently associated with CV events in patients with CAD.

Conclusion

Serum leptin levels could serve as a biomarker for future CV events in patients with CAD.

Fasting serum resistin level positively correlates with metabolic syndrome in patients on peritoneal dialysis

Resistin is an adipocyte-derived polypeptide that provides a link between obesity and insulin resistance. The aim of this study was to explore the relationship between fasting serum resistin levels and the metabolic syndrome (MetS) among patients on peritoneal dialysis (PD). Fasting blood samples were obtained from 51 patients on PD. According to the diagnostic criteria of the International Diabetes Federation, 28 (54.9%) patients had MetS. Fasting resistin levels positively correlated with MetS among patients on PD (P = 0.001). On multivariate logistic regression analysis, resistin remained a significant independent predictor of MetS (odds ratio [OR]: 1.103, 95% confidence interval: 1.011-1.203, P = 0.027). Univariate linear analysis showed that waist circumference (P = 0.015), body mass index (BMI; P = 0.001), body fat mass (P = 0.001), triglycerides (P = 0.003), logarithmically transformed insulin (log-insulin; P = 0.003), and logarithmically transformed homeostasis model assessment of insulin resistance (P = 0.003) were positively correlated and high-density lipoprotein-cholesterol (P = 0.021) was negatively correlated with fasting serum resistin levels. Multivariate forward stepwise linear regression analysis of significant variables showed that body fat mass (β = 0.454, adjusted R² change = 0.190, P = 0.001) was an independent predictor of fasting serum resistin levels in patients on PD. Resistin levels are significantly increased in patients on PD with MetS. Body fat mass is an independent predictor of serum resistin levels in such patients.

Here, there and everywhere: Resistin-like molecules in infection, inflammation, and metabolic disorders

The Resistin-Like Molecules (RELM) α, β, and γ and their namesake, resistin, share structural and sequence homology but exhibit significant diversity in expression and function within their mammalian host. RELM proteins are expressed in a wide range of diseases, such as: microbial infections (eg. bacterial and helminth), inflammatory diseases (eg. asthma, fibrosis) and metabolic disorders (eg. diabetes). While the expression pattern and molecular regulation of RELM proteins are well characterized, much controversy remains over their proposed functions, with evidence of host-protective and pathogenic roles. Moreover, the receptors for RELM proteins are unclear, although three receptors for resistin, decorin, adenylyl cyclase-associated protein 1 (CAP1), and Toll-like Receptor 4 (TLR4) have recently been proposed. In this review, we will first summarize the molecular regulation of the RELM gene family, including transcription regulation and tissue expression in humans and mouse disease models. Second, we will outline the function and receptor-mediated signaling associated with RELM proteins. Finally, we will discuss recent studies suggesting that, despite early misconceptions that these proteins are pathogenic, RELM proteins have a more nuanced and potentially beneficial role for the host in certain disease settings.