Skin autofluorescence in the general population: associations and prediction
van Waateringe, Robert Paul
IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below.
Document Version
Publisher's PDF, also known as Version of record
Publication date: 2019
Link to publication in University of Groningen/UMCG research database
Citation for published version (APA):
van Waateringe, R. P. (2019). Skin autofluorescence in the general population: associations and prediction. Rijksuniversiteit Groningen.
Copyright
Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons).
Take-down policy
If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.
Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons the number of authors shown on this cover page is limited to 10 maximum.
7
Skin autofluorescence, a non-invasive biomarker for
advanced glycation end products, is not related to the
number of pregnancies
To the editor
The role of advanced glycation endproducts (AGEs) in the pathophysiology of diabetes related complications and ageing has been studied extensively. AGEs represent chronic exposure to hyperglycemia and oxidative stress. Tissue AGE accumulation can be assessed non-invasively by measuring autofluorescence of the skin (SAF) with a so-called AGE reader. Markers of oxidative stress are elevated during pregnancy, which can, in turn, increase the formation of AGEs (1). One study reported that SAF levels were higher in pregnant women with preexistent diabetes than in women with gestational diabetes and women without diabetes (2). Preliminary data from our group suggested that SAF levels increase during pregnancy, and do not return to levels found before pregnancy (Groen et al. unpublished data). This phenomenon may be caused by increased oxidative and glycemic stress during pregnancy. Therefore, the aim of the present study was to assess the relationship between SAF and the number of pregnancies.
Methods
Subjects included in the study were participants from the Lifelines Cohort Study, a large population-based cohort study in the northern region of the Netherlands (www.lifelines. net, accessed 24 December 2017). The Lifelines study was approved by the Medical Ethics Committee of the University Medical Center Groningen. Written informed consent was obtained from all participants. The present study included women of Western European descent aged between 18 and 80 years for whom an SAF measurement was available. Subjects with type 1 and type 2 diabetes were excluded, as were as those with missing data for diabetes, leaving 47 834 individuals for analysis. Subjects completed a questionnaire on medical history, past and current diseases, use of medication, and health behavior. The questionnaire also included information on previous pregnancies and childbirth. Women were asked how many times they had been pregnant and how many children were born. In the present study, SAF was calculated as the mean of three consecutive measurements using an AGE Reader (DiagnOptics (3). Age-adjusted SAF (Z-scores) was calculated because SAF is strongly affected by aging (3). Data are given as the mean ± SD or as the median with interquartile range (IQR) in the case of non-normally distributed data. Linear regression analysis was performed to examine the association between the number of pregnancies and SAF. In the multivariate models, we adjusted for relevant factors, such as waist circumference, body mass index (BMI), renal function, and smoking. Two-tailed P < 0.001was considered significant.
Results
The clinical characteristics of the study population are given in Table S1, available as Supplementary Material to this paper. Mean subject age was 44 ± 12 years, mean waist circumference was 87 ± 12 cm, and mean BMI was 25.8 ± 4.6 kg/m2. The median number of pregnancies was 2.0 (IQR 1.0–3.0). In total, 20.5% of women had not been pregnant, 42% reported one to two pregnancies, 30% reported three to four pregnancies, and 7.5% reported five or more pregnancies. A higher number of pregnancies was associated with higher SAF, which persisted after correction for waist circumference and renal function (P < 0.0001). However, after further correction for age, SAF was no longer associated with the number of pregnancies (P = 0.713; Table 1). Fig. 1 shows that SAF Z-scores are comparable in the various groups of women divided according to the number of pregnancies. Women in the highest quartile of the SAF Z-score had a higher prevalence of metabolic syndrome, as well as higher BMI, waist circumference, glucose, HbA1c, and lipids (all P < 0.01) than women in the other three quartiles, and a similar number of pregnancies compared with those in the lowest quartile (Table S2).
Figure 1. Number of pregnancies and age-corrected skin autofluorescence (SAF Z-score)
The boxes show the interquartile range, with the median value indicated by the horizontal line; whiskers showthe range. Dots indicate outliers.
Table 1. Univariate and multivariate analyses for SAF
Model Parameters Β P Value R² (%)
1 Number of pregnancies 0.061 < 0.0001 5.3 2 Number of pregnancies 0.003 0.800 30.7 Age 0.020 <0.0001 3 Number of pregnancies 0.003 <0.0001 19.7 Waist circumference 0.013 <0.0001 GFR -0.006 <0.0001 4 Number of pregnancies 0.030 <0.0001 20.5 Waist circumference 0.012 <0.0001 GFR -0.006 <0.0001 Diabetes 0.084 <0.0001 5 Number of pregnancies -0.001 0.941 31.3 Age 0.017 <0.0001 Waist circumference 0.004 <0.0001 GFR -0.001 <0.0001 Diabetes 0.015 <0.0001
Discussion
After correction for important confounders, SAF increased with the number of pregnancies in women from the general population. However, after correction for age, this association was no longer significant. The increased oxidative stress that occurs during pregnancy may significantly affect SAF measurements. Indeed, it has been reported that SAF is elevated in women with pre-eclampsia and associated with increased carotid artery intima–media thickness, a marker for atherosclerosis (4). Moreover, SAF was associated with higher blood pressure, triglycerides, and C-reactive protein levels, indicating the potential cardiovascular risk associated with these factors (5). Therefore, we postulate that the effect of pregnancy on SAF may only be restricted to pathological pregnancies, such as those complicated by pre-eclampsia (4, 5). Unfortunately, the Lifelines dataset did not record any complications of pregnancy.
Two important studies have reported on the association between reproductive history and cardiovascular health. One of these studies reported that a higher number of pregnancies was associated with lower cardiovascular mortality (6) whereas the other study showed that the number of pregnancies or live births was associated with higher left ventricular mass and end-systolic volume (7). A recent review suggested that pre-eclampsia is an under-recognized risk factor for IHD, chronic hypertension, peripheral vascular disease, and stroke (8).
In conclusion, in the present study SAF increased with a higher number of pregnancies, but not after correction for participants’ age. Those with the highest age-corrected SAF had a worse risk factor profile for future cardiovascular disease.
Acknowledgement
The authors wish to acknowledge all participants of the LifeLines Cohort Study and everybody involved in the set-up and implementation of the study.
Funding
Lifelines has been funded by a number of public sources, notably the Dutch Government, The Netherlands Organization of Scientific Research NOW [grant 175.010.2007.006], the Northern Netherlands Collaboration of Provinces (SNN), the European fund for regional development, Dutch Ministry of Economie Affairs, Pieken in de Delta, Provinces of Groningen and Drenthe, the Target project, BBMRI-NL, the University of Groningen, and the University Medical Center Groningen, The Netherlands. This work was supported by the National Consortium for Healthy Ageing, and funds from the European Union’s Seventh Framework program (FP7/2007-2013) through the BioSHaRE-EU (Biobank Standardisation and Harmonisation for Research Excellence in the European Union) project, grant agreement 261433. LifeLines (BRIF4568) is engaged in a Bioresource research impact factor (BRIF) policy pilot study, details of which can be found at: https:// www.bioshare.eu/content/bioresource-impact-factor
Disclosure
None declaredReferences
1. Toescu V, Nuttall SL, Martin U, Kendall MJ, Dunne F. Oxidative stress and normal pregnancy.
Clin Endocrinol (Oxf) 2002; 57: 609-13.
2. De Ranitz-Greven WL, Kaasenbrood L, Poucki WK, Hamerling J, Bos DC, Visser GH, et al. Advanced glycation end products, measured as skin autofluorescence, during normal pregnancy and pregnancy complicated by diabetes mellitus. Diabetes Technol Ther. 2012;
14: 1134-9.
3. Meerwaldt R, Graaff R, Oomen PHN, Links TP, Jager JJ, Alderson NL, et al. Simple noninvasive assessment of advanced glycation endproduct accumulation. Diabetologia 2004; 47:
1324-30.
4. Blaauw J, Smit AJ, van Pampus MG, van Doormaal JJ, Aarnoudse JG, Rakhorst G, et al. Skin autofluorescence, a marker of advanced glycation end products and oxidative stress, is increased in recently preeclamptic women. Am J Obstet Gynecol. 2006; 195: 717-22.
5. Coffeng SM, Blaauw J, Souwer ET, Rakhorst G, Smit AJ, Graaff R, et al. Skin
autofluorescence as marker of tissue advanced glycation end-products accumulation in formerly preeclamptic women. Hypertens Pregnancy. 2011; 30: 231-42.
6. Jacobs MB, Kritz-Silverstein D, Wingard DL, Barrett-Connor E. The association of
reproductive history with all-cause and cardiovascular mortality in older women: the Rancho Bernardo Study. Fertil Steril. 2012; 97: 118-24.
7. Parikh NI, Lloyd-Jones DM, Ning H, Ouyang P, Polak JF, Lima JA, et al. Association of number of live births with left ventricular structure and function. The Multi-Ethnic Study of Atherosclerosis (MESA). Am Heart J. 2012; 163: 470-6.
8. Ahmed R, Dunford J, Mehran R, Robson S, Kunadian V. Pre-eclampsia and future cardiovascular risk among women: a review. J Am Coll Cardiol. 2014; 63: 1815-22.
SUPPLEMENTAL DATA
Supplemental Table 1. Baseline characteristics of the participating women
N 46828
Age (years) 44 ± 12
Body mass index (kg/m²) 25.8 ± 4.6 Waist circumference (cm) 87 ± 12
Systolic / diastolic blood pressure (mmHg) 123 ± 16 / 72 ± 9 Total cholesterol (mmol/L) 5.0 ± 1.0 HDL cholesterol (mmol/L) 1.61 ± 0.39 LDL cholesterol (mmol/L) 3.1 ± 0.9 Triglycerides (mmol/L) 0.88 (0.66-1.21) Creatinine clearance (ml/min) 112 ± 30 Glucose (mmol/l) 4.8 ± 0.5 HbA1c (%) 5.5 ± 0.3 Number of pregnancies 0 1-2 3-4 >4 2.1 ± 1.6 9129 (20.5) 18673 (42) 14076 (30) 2666 (7.5) Biological children Son Daughter 2.3 ± 0.9 1.2 ± 0.9 1.2 ± 0.9 Smoking status Never smokers Ex-smokers Current smokers 22133 (47) 14806 (32) 8981 (19) 908 (2) Pack-years Ex-smokers Current smokers 5.5 (2.2-11.0)12.0 (5.9-19.5) Coffee consumption (cups per day) 2.8 (1.3-4.7)
SAF (AU) 1.88 ± 0.43
SAF Z score (age-adjusted) -0.02 ± 0.83
Supplemental Table 2. SAF Z-scores and cardiovascular risk factors Quartile SAF Z-score
1 2 3 4
Age (yrs) 47 ± 13 42 ± 12 43 ± 12 46 ± 12 * BMI (kg/m2) 25.6 ± 4.2 25.5 ± 4.5 25.8 ± 4.7 26.2 ± 5.0 * Waist circumference (cm) 86 ± 11 86 ± 12 87 ± 12 88 ± 13 * Systolic blood pressure (mmHg) 123 ± 16 122 ± 15 123 ± 15 123 ± 15 Diastolic blood pressure (mmHg) 72 ± 9 72 ± 9 72 ± 9 73 ± 9 * Total cholesterol (mmol/L) 5.1 ± 1.0 4.9 ± 1.0 5.0 ± 1.0 5.1 ± 1.0 * HDL-cholesterol (mmol/L) 1.65 ± 0.39 1.61 ± 0.38 1.59 ± 0.39 1.58 ± 0.40 * Triglycerides (mmol/L) 0.99 ± 0.57 0.98 ± 0.52 1.02 ± 0.59 1.08 ± 0.59 * Glucose (mmol/L) 4.8 ± 0.5 4.8 ± 0.5 4.8 ± 0.5 4.9 ± 0.5 * metabolic syndrome % 10 10 11 15 * Number of pregnancies 2.2 ± 1.5 2.0 ± 1.6 2.0 ± 1.6 2.2 ± 1.6 * P<0.001 vs other quartile groups
