Skin autofluorescence in the general population: associations and prediction
van Waateringe, Robert Paul
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Publication date: 2019
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van Waateringe, R. P. (2019). Skin autofluorescence in the general population: associations and prediction. Rijksuniversiteit Groningen.
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Introduction and aim of the thesis
1
Introduction
Advanced glycation end products
Advanced glycation end products (AGEs) are a group of very heterogeneous compounds formed by non-enzymatic glycation of proteins, lipids and nucleic acids under conditions of glycaemic, oxidative or carbonyl stress (1). This mechanism of AGE formation is also called the Maillard or browning reaction (2). In short, the interaction between the carbonyl groups of reducing sugars and free amino groups of proteins leads to the formation of a Schiff base. Rearrangement of the Schiff base results in Amadori products. A well-known example of an Amadadori product is glycated haemoglobin which is commonly used in clinical practice to asses long-term diabetes control. The slow process of oxidation of the Amadori products leads to reactive carbonyl compounds and subsequently to the formation of AGEs (3, 4). Reactive oxygen species (ROS) are also involved in the lipid peroxidation pathway, altering lipids in reactive carbonyl compounds. This reaction results in the formation of advanced lipoxidation end products (ALEs) (5, 6).
Next to endogenous formation of AGEs, there are also exogenous sources of AGEs such as tobacco smoke and certain foods. Tobacco smoke itself contains high levels reactive glycation products (7). In addition, tobacco smoke causes oxidative stress, which in turn can enhance the formation of AGEs. High levels of AGEs were observed in lenses and blood vessels of tobacco smokers (8). A second exogenous source of AGEs is the modern diet. Intake of food containing high levels of AGEs may lead to an increase of AGEs. Uncooked, animal derived food, rich of protein and fad, generally contain high levels of AGEs (9). However, more important is the way how food is processed. Especially the preparation and prolonged heating of food plays an key role in the generation of AGEs, including grilling, roasting and boiling (9, 10). It has been estimated that approximately 10% of AGEs from food are absorbed from the gastro-intestinal tract into the circulation (11).
AGEs are known to accumulate in the body during ageing (12). The lifetime of AGEs depends on the specific protein on which the AGEs are cross-linked. It has been reported that AGEs reflect long-term (~ 15 years) accumulation of glycaemic and oxidative stress, and might therefore be considered as a marker of ‘metabolic memory’ (13). In people with diabetes, both the formation and accumulation of AGEs is increased as a result of chronic hyperglycaemia (14, 15). In individuals with impaired renal function, the formation of AGEs may be a result of oxidative or carbonyl stress (16, 17), while decreased renal clearance of serum AGEs also contributes to increased accumulation of AGEs (16, 18).
Introduction and aim of the thesis 13 In diabetes, accumulation of AGEs is associated with both micro- and macrovascular complications (19). Accumulation of AGEs in the kidney may cause thickening of the capillary basement membrane and sclerosis of the glomeruli (20). Increased accumulation of AGEs in the axoplasm of myelinated and unmyelinated neurons and Schwann cells supports its involvement in the development and progression of diabetic neuropathy (21). Accumulation of AGEs induce the production of vascular endothelial growth factor (VEGF), monocyte chemotactic protein-1 (MCP-1), and transforming growth factor-b (TGF-b), which are key cytokines related to the development of diabetic retinopathy (22, 23). Cross-linking of proteins within the vascular wall will reduce vascular elasticity and increase arterial stiffness (24, 25). In contrast, treatment with AGEs breakers for 1-3 weeks has been shown to effectively reverse arterial stiffness in rats with streptozotocin-induced diabetes (26). AGEs accumulation have also been found in carotid atherosclerotic plaques which underlines that accumulation of AGEs is involved in the development of atherosclerosis (27).
Furthermore, binding of AGEs to its receptor (RAGE) might play a role in the development of diabetes cardiovascular complications. Activation of RAGE causes intracellular signaling which leads to a cascade of pro-inflammatory cytokines including nuclear factor-kappa B, interleukin 6 and tumor necrosis factor alpha (28, 29). Furthermore, it stimulates smooth muscle cell proliferation, increases oxidative stress and causes endothelial dysfunction (28, 30).
Non-invasive measurement of skin AGEs
In the past, several investigators have tried to assess AGE levels in the blood and in tissues obtained by (skin) biopsies. However, this method is invasive, time-consuming and associated with high costs. Measurement of AGEs is nowadays performed using a device that is called the AGE Reader (Diagnoptics). This device is developed in Groningen, The Netherlands. It estimated skin AGE content non-invasively based on its fluorescent characteristics of many AGE compounds (31). Therefore, measuring skin AGEs using its fluorescent capacities is called skin autofluorescence (SAF). The measurement of SAF is easily performed in the office on the volar side of the forearm, 10cm below the elbow. The AGE Reader illuminates a skin surface of approximately 4 cm², guarded against surrounding light, with an excitation light source with a wavelength between 300 and 420nm (peak intensity at ~ 370nm). Emission light and reflected excitation light from the skin are measured with an internal spectrometer in the range 300 to 600nm. SAF is calculated by dividing the average emitted light intensity per nanometer in the range of 420-600 nm by the average excitated light intensity per nanometer in the range
420 nm and multiplied by 100. SAF levels are expressed in arbitrary units and increase or decrease per arbitrary unit (AU). It has been shown that SAF levels correlate well with tissue AGEs measured in skin biopsies from subjects with and without diabetes (31, 32). Intra-individual variance among diabetic and control subjects was estimated at around 5% when repeated SAF measurement were taken over a single day (31). SAF levels positively correlate with ageing and are higher among subjects with diabetes and impaired renal function (33).
Skin autofluorescence and previous studies
Over the past 10 years, many studies have been performed using SAF as a biomarker for several clinical conditions, including type 2 diabetes, renal failure and several cardiovascular diseases. Among subjects with type 2 diabetes, higher SAF levels were associated with both micro-and macrovascular complications, and with the severity of diabetes-related complications (34, 35). Furthermore, SAF have been demonstrated to be a strong predictor for cardiac mortality among subjects with type 2 diabetes (36). Addition of SAF measurement to the United Kingdom Prospective Diabetes Study (UKPDS) risk score resulted in re-classification of around 25% of the study population from the low-risk to the high-low-risk group (37). The clinical value of SAF has also been studied in subjects with renal failure. A Japanese study reported that high SAF levels are associated with the progression of chronic kidney disease (38). Other studies have shown that SAF predicts both overall and cardiovascular mortality among (pre)hemodialysis patients (39-41). Furthermore, SAF independently predicts chronic graft dysfunction in renal transplant recipients (42). Only a small number of studies have investigated SAF in subjects without diabetes or impaired renal function. It has been shown that SAF levels are elevated in subjects with (sub-clinical) atherosclerosis and acute ST elevated myocardial infarction, whereas a SAF above the median was of predictive value for future cardiovascular events (43, 44). SAF levels are elevated in subjects with stable coronary artery heart disease and associated with carotid artery intima media thickness (45, 46). Furthermore, SAF levels are higher in individuals with carotid artery stenosis and peripheral artery disease and associated with 5-years risk of mortality and cardiovascular events (47, 48).
Outline of thesis
Most previous research on SAF has focused on populations with either type 2 diabetes, peripheral artery disease, or (end-stage) renal failure. In this thesis, we aim to describe the association between skin autofluorescence and cardiometabolic risk factors in the general population. For these studies, we use data collected in people participating in
Introduction and aim of the thesis 15 the Dutch LifeLines Cohort Study. In addition, we evaluate whether skin autofluorescence is able to predict incident type 2 diabetes, cardiovascular disease and overall mortality within the general population.
The formation and accumulation of AGEs is a complex pathway including either endogenous as well as exogenous pathways. Moreover, when measuring skin autofluorescence, many factors have to be taken into account. Therefore, we describe both clinical and lifestyle determinants of skin autofluorescence among subjects with and without type 2 diabetes in chapter 2. Tobacco smoking is an exogenous source of AGEs accumulation and higher SAF levels are shown in individuals who smoke. However, the effect of secondhand smoking and smoking cessation on AGEs accumulation needs to be determined. The results of this study are presented in chapter 3. The metabolic syndrome is a combination of several cardiometabolic abnormalities associated with a higher risk of both cardiovascular disease and type 2 diabetes. Explorative associations between skin autofluorescence and the individual metabolic syndrome components are shown in chapter 4. In chapter 5 we evaluate the predictive value of skin autofluorescence as a biomarker for incident type 2 diabetes, cardiovascular disease and overall mortality. Next, we assess the association between thyroid hormone levels and incident type 2 diabetes, cardiovascular disease and overall mortality in the general population and whether the association is independent of SAF. The results are shown in chapter 6. Inflammation plays an essential role in the development of insulin resistance, type 2 diabetes and atherosclerosis. Preliminary data from our group showed that SAF levels increase during pregnancy, and do not return to levels found before pregnancy (Groen et al. unpublished data). This may be caused by increased oxidative and glycemic stress during pregnancy. In chapter 7 we examined the relationship between SAF and the number of pregnancies. In chapter 8 we assessed the reproducibility and standardization of several inflammatory biomarkers, including hsCRP, hsIL6 and TNFα, taking into account the influence of assay variability, the reproducibility of a specific measurement between laboratories as well as the influence of sample storage and storage time. In chapter 9 we summarize and discuss the separate chapters and reflect on possible future research on SAF in the general population, and its current application in screening for incident type 2 diabetes, cardiovascular disease and mortality.
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Introduction and aim of the thesis 19
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