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Open Access

Peer-reviewed

Research Article

Are soluble E-selectin, ICAM-1, and VCAM-1 potential predictors for the development of diabetic retinopathy in young adults, 15–34 years of age? A Swedish prospective cohort study

  • Charlotte Ekelund ,

    Roles Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing

    charlotte.nagelius_ekelund@med.lu.se

    Affiliation Diabetes Research Laboratory, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden

    ⨯
  • Jonatan Dereke,

    Roles Conceptualization, Formal analysis, Investigation, Methodology, Writing – review & editing

    Affiliation Diabetes Research Laboratory, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden

    ⨯
  • Charlotta Nilsson,

    Roles Formal analysis, Writing – review & editing

    Affiliations Diabetes Research Laboratory, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden, Department of Pediatrics, Helsingborg Hospital, Helsingborg, Sweden

    ⨯
  • Mona Landin-Olsson

    Roles Conceptualization, Formal analysis, Resources, Supervision, Validation, Writing – review & editing

    Affiliations Diabetes Research Laboratory, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden, Department of Endocrinology, Skåne University Hospital, Lund, Sweden

    ⨯

Abstract

The aim of this study was to determine plasma levels of three adhesion molecules that may contribute to the development of diabetic retinopathy; soluble endothelial selectin (sE-selectin), soluble intercellular adhesion molecule-1 (sICAM-1), and soluble vascular cell adhesion molecule-1 (sVCAM-1), in young adults, aged 15–34 years at diagnosis of diabetes, to find potential predictors for development of retinopathy, and to evaluate their relation to diabetes associated autoantibodies. Participants with type 1 (n = 169) and type 2 diabetes (n = 83) were selected from the complications trial of the Diabetes Incidence Study in Sweden and classified in two subgroups according to presence (n = 80) or absence (n = 172) of retinopathy as determined by retinal photography at follow-up 8–10 years after diagnosis of diabetes. Blood samples were collected at diagnosis in 1987–88. The levels of sE-selectin, sICAM-1, and sVCAM-1 were analysed by enzyme-linked immunosorbent assay and islet cell antibodies by a prolonged two-colour immunofluorescent assay. Mean HbA1c (p<0.001) and clinical characteristics: mean body mass index (p = 0.019), systolic blood pressure (p = 0.002), diastolic blood pressure (p = 0.003), male gender (p = 0.026), and young age at diagnosis of diabetes (p = 0.015) remained associated with development of retinopathy in type 1 diabetes. However, in a multivariate analysis only HbA1c remained as a risk factor. sE-selectin was significantly higher in the group with type 2 diabetes and retinopathy, compared to the group with type 2 diabetes without retinopathy (p = 0.04). Regarding sE-selectin, sICAM-1, and sVCAM-1 in participants with type 1 diabetes, no differences were observed between the groups with or without retinopathy. This trial confirmed the role of HbA1c and clinical characteristics as predictors for development of retinopathy in type 1 diabetes. sE-selectin stands out as a potential predictor for development of retinopathy in type 2 diabetes, whereas a predictive role for sICAM-1 and sVCAM-1 could not be identified neither for type 1 nor type 2 diabetes.

Citation: Ekelund C, Dereke J, Nilsson C, Landin-Olsson M (2024) Are soluble E-selectin, ICAM-1, and VCAM-1 potential predictors for the development of diabetic retinopathy in young adults, 15–34 years of age? A Swedish prospective cohort study. PLoS ONE 19(6): e0304173. https://doi.org/10.1371/journal.pone.0304173

Editor: Tomislav Bulum, Medical School, University of Zagreb, CROATIA

Received: November 26, 2023; Accepted: May 8, 2024; Published: June 6, 2024

Copyright: © 2024 Ekelund et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Data cannot be shared publicly because of ethical restrictions imposed by the Regional Ethical Review Board, Lund, Sweden. The authors must ensure that the privacy of the participants in this study is preserved. The number of participants is limited. Hence, the authors cannot provide sensitive patient data that enables potential identification of the participants. If required, the corresponding author of this paper or the Diabetes Research Laboratory, B11 BMC, Lund University, 221 84 Lund, Sweden (contact person: Dr Mona Landin-Olsson, phone number +46707195264, e-mail mona.landin-olsson@med.lu.se), are available for inquiries and requests regarding the data for researchers who meet the criteria for access to confidential data. Data requests may also be sent to Etikprövningsmyndigheten, Box 2110, 750 02, Uppsala, Sweden (phone number +46104750800, e-mail registrator@etikprovning.se).

Funding: CE received funding for this study from the Stig and Ragna Gorthon Foundation (grant number 2015-1262), https://www.gorthonstiftelsen.se, and Capio Forskningsstiftelse (grant number 2018-3175 and 2019-3289), https://www.gudok.gu.se. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: When the research was conducted, Jonatan Dereke was affiliated to Lund University. Thereafter, he has been employed by Novo Nordisk Scandinavia AB in Malmö, Sweden. Charlotte Ekelund, Charlotta Nilsson and Mona Landin-Olsson have declared that no competing interests exist.

Introduction

The incidence of childhood type 1 diabetes mellitus (T1DM) has increased worldwide with Sweden having the highest incidence in the world next to Finland [1, 2]. Even the burden of type 2 diabetes mellitus (T2DM) in children and adolescents is substantial [3]. Due to severe complications later in life, diabetes mellitus (DM) causes major morbidity and mortality. About a third of people with DM have signs of diabetic retinopathy (DR), and even more for people with T1DM, which can lead to impairment or loss of vision [4, 5]. The prevalence of DR among adolescents and young adults with T1DM and T2DM has been reported as 5.6% and 9.1%, respectively, in the SEARCH study with a mean DM duration of 7.9 years [6], and as 3.4% and 6%, respectively, in a more recent study with a mean DM duration of 4.1 years for T1DM and 1.1 years for T2DM [7], i.e., a declining trend for T1DM due to intensive treatment with optimized glycemic control [8]. There is a concern for increasing prevalence of T2DM and DR. For adolescents and young adults with T2DM with mean DM duration 11 years, the TODAY follow-up study has reported a prevalence of DR as per 51.0% in 2017–2018 compared to 13.7% seven years earlier [9]. Hyperglycemia, DM duration, hypertension, dyslipidemia, puberty, pregnancy, and ethnic origin are important risk factors for development and progression of DR [4, 5, 9–13], but findings regarding gender and body mass index (BMI) have been inconsistent. According to the Diabetes Incidence Study in Sweden (DISS), the prevalence of DR seemed to be higher in men [14], whereas other studies could not show such a difference between the genders [4, 15–18]. Furthermore, DISS has shown an association between BMI and DR among young patients with DM [14] while studies performed in Finland and the US have not [15, 17]. The TODAY study among youth with T2DM showed a lower prevalence of DR in the most severely obese participants, after adjustment for age, hemoglobin A1c (HbA1c) and DM duration [18].

Studies of circulating biomarkers of inflammation and endothelial dysfunction have indicated predictive value for development of DR [19, 20]. Hyperglycemia enhances leucocyte adhesion to the endothelium via upregulation of adhesion molecules such as soluble endothelial selectin (sE-selectin), soluble intercellular adhesion molecule-1 (sICAM-1) and soluble vascular cell adhesion molecule-1 (sVCAM-1) [21, 22]. This inflammatory activity and endothelial dysfunction have been considered of importance in the pathogenesis of DR [23, 24]. Soluble forms of adhesion molecules released by the affected endothelium are detectable in plasma. Increased expression of sE-selectin, sICAM-1, and sVCAM-1 have been found in patients with T1DM/T2DM and DR in comparison with patients without DR [19, 25–27]. In addition, the expression of sE-selectin and sVCAM-1 in patients with T1DM and T2DM seemed to increase with progression of DR and could thus relate to the severity of DR [28, 29]. A meta-analysis has revealed increased levels of sICAM-1 in patients with DR irrespective of type of diabetes as well as a possible association with the severity of DR [30]. In a prospective study of inflammatory biomarkers at diagnosis of DM and risk of DR in T1DM in the Diabetes Control and Complications Trial (DCCT), sICAM-1 may have been associated with the development of retinal hard exudates, but neither sICAM-1 nor sVCAM-1 were significantly associated with progression of DR [31]. Another prospective study, investigating the DCCT/Epidemiology of Diabetes Interventions and Complications study (EDIC) cohort and risk of DR in T1DM, has reported an association between increased levels of sE-selectin at diagnosis of DM and development of DR, but not for sICAM-1 and sVCAM-1 [32]. Thus, previous studies have been contradictory. In a study of T2DM patients, no differences could be found in the levels of sE-selectin, sICAM-1, and sVCAM-1 between patients with and without DR, and no associations to progression of DR were identified [33]. In a group with T2DM and DR, sE-selectin was not significantly higher neither compared to patients with T2DM without DR, nor to healthy control subjects [34]. As previously mentioned, sE-selectin has been associated with progression of DR in patients with T2DM [29]. However, yet another study in T2DM showed that this association was not independent of glycemic control and BMI [35].

Published data reflect the presence of DR and high levels of soluble adhesion molecules, although with inconsistencies. Due to the role of adhesion molecules in endothelial activation, their increased levels could potentially indicate the risk for, and severity of, DR development. The primary aim of this study was to determine plasma levels of sE-selectin, sICAM-1, and sVCAM-1 in young adults at diagnosis of DM, to find potential predictors for the development of DR. The secondary aim was to evaluate the adhesion molecules’ relation to diabetes associated autoantibodies in the complications trial of the Diabetes Incidence Study in Sweden (K-DISS) cohort. If an association between sE-selectin, sICAM-1, and/or sVCAM-1 and DR can be identified, and hence these biomarkers could be used at an early stage for prediction of DR, high-risk patients for the development of DR could be recognised. Healthcare could then be individualised with resources and screening programmes focusing on patients with the biggest needs. Hopefully, the onset of DR can be prevented or delayed, providing benefits not only for the individual but also for society and the payers.

Materials and methods

The Diabetes Incidence Study in Sweden (DISS)

Since 1983, a nationwide population-based prospective study, DISS, registers the incidence of DM, except gestational diabetes, and its complications in the age group 15–34 years. The objective of DISS is to identify factors relevant for the development of DM and its complications [36]. Data from DISS have been used in the sub study K-DISS, previously described in detail, to investigate the prevalence of DR [14] and diabetic kidney disease [37, 38] at follow-up. Part of those results were used in this study [14].

Study population

The study population consisted of all patients (n = 363), participating in K-DISS, diagnosed by clinicians as T1DM (n = 226) or T2DM (n = 137), according to the World Health Organization criteria [39], in 1987–88 at an age of 15–34 years. The classification of T1DM was made by islet cell antibodies (ICA) and/or clinical characteristics and patients presenting without ICA were classified as T2DM. Patients who developed nephropathy (n = 13) or concomitant nephropathy and DR (n = 10) during follow-up were subsequently excluded in order not to risk investigating patients with nephropathy caused by conditions unrelated to DM. Three patients were excluded due to incorrect registration in the registry. At follow-up 8–10 years after diagnosis of DM, 114 out of 337 participants had developed any grade of DR, but no other complications. The remaining 223 participants without DR, or any other complications, constituted the control group. 34 blood samples in the group with DR and 51 blood samples in the control group contained insufficient volume of blood for the tests to be conducted. Hence, in total 80 participants in the group with DR and 172 participants in the control group were investigated. Classification of DR was performed by dilated retinal photography in most cases, by ophthalmoscopy or slit-lamp bio-microscopy data from medical records if no photographs had been taken, and the 11-step scale of the alternative classification of the Wisconsin study [14, 40]. The median number of eye examinations by photography was three per participant, without any difference between T1DM and T2DM. All photographs taken since diagnosis of DM were centrally assessed by two independent and experienced graders. The severity of DR was determined by the eye most severely affected. Height and weight for calculation of BMI, as well as systolic and diastolic blood pressure (BP), were reported at follow-up. All HbA1c values since diagnosis were requested. Tobacco use was defined as current or previous daily use. The recruitment process of study participants is described in Fig 1.

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Fig 1. The recruitment process of study participants.

K-DISS, complications trial of the Diabetes Incidence Study in Sweden; DR, diabetic retinopathy.

https://doi.org/10.1371/journal.pone.0304173.g001

Analyses

Sample handling.

At diagnosis of DM blood samples were collected in tubes containing ethylenediaminetetraacetic acid (EDTA) and sent by mail from hospitals and primary health care centres in Sweden to the central laboratory for analyses. Plasma was separated by centrifugation at 2000 x g and stored at a temperature of -80°C until analysis of the adhesion molecules. ICA were determined, in serum samples collected at diagnosis of DM, by a prolonged two-colour immunofluorescent assay at Malmö General Hospital [41, 42], and have previously been reported [43]. HbA1c was measured at local laboratories using ion-exchange chromatography and presented as a percentage as per the National Glycohemoglobin Standardization Program (NGSP) and later converted to mmol/mol as per the International Federation of Clinical Chemistry (IFCC) units. The mean HbA1c value during the entire follow-up period was calculated for each participant.

Laboratory analyses.

The plasma concentrations of the soluble adhesion molecules were determined using the enzyme-linked immunosorbent assay ELISA DuoSet (R&D Systems, Minneapolis, MN, USA), according to the manufacturer’s instructions. Plasma samples were diluted 1:25 for sE-selectin, 1:200 for sICAM-1, and 1:1000 for sVCAM-1. Samples from participants with and without DR were alternated on each ELISA microplate to reduce interassay variability and measured in duplicate. Two in-house plasma controls were added to each run. For absorbance measurements at 450 nm and 580 nm, a FLUOstar Optima Microplate Reader (BMG LABTECH, Ortenberg, Germany) was used. A four-parametric logistic regression standard curve was used to calculate the concentrations. In this study, the intraassay coefficients of variation were 2.8% for sE-selectin, 4.3% for sICAM-1, and 3.3% for sVCAM-1. The lower detection limits of the assays were 1.5 ng/ml for sE-selectin, 5.1 ng/ml for sICAM-1, and 33.8 ng/ml for sVCAM-1.

Ethics

The study was approved by the Regional Ethical Review Board, Lund, Sweden, (LU 176–03 and LU 2009–423) and performed in accordance with the Declaration of Helsinki. Written information about the objective of the study was provided before inclusion and each participant gave written informed consent. For minors, written informed consent was obtained from parents or guardians. The authors had access to information that could identify individual participants after data collection. Data were accessed 26-Sep-2016 for research purposes.

Statistical analyses

All HbA1c values since diagnosis of DM were used when calculating the mean HbA1c using the area under the curve of HbA1c over time to compensate for the occasionally irregular intervals between the measurements.

The D’Agostino-Pearson test was used to examine normal distribution of data. Results that were normally distributed are presented as mean ± standard deviation (SD). The t-test was used for comparison between groups. The non-parametric variables, i.e., results not normally distributed, are presented as median and interquartile range and the Mann-Whitney U test was used for comparison between groups. Frequencies are presented as numbers and percent and were compared using the chi-squared test. Correlations between variables were determined using Spearman’s rank correlation test and presented with 95% confidence intervals (CI). Logistic regression was used to analyse the effect of several independent variables on DR. Only statistically significant variables were included in a multivariate analysis model. Statistical analyses were performed using MedCalc for Windows (version 12.7.0.0, MedCalc Software, Ostend, Belgium). P-values below 0.05 were considered statistically significant.

Results

In the study population of 252 participants, 80 (31.7%) had developed DR and 172 (68.3%) had not developed DR 8–10 years after diagnosis of DM. Participants with DR had statistically significant higher mean HbA1c (70.4±15.2 vs. 60.7±13.8 mmol/mol; p<0.0001), mean BMI (24.7(23.1–27.0) vs. 24.0(21.6–26.5) kg/m2; p = 0.03), systolic BP (124±10.5 vs. 120±11.9 mm Hg; p = 0.02) and diastolic BP (76.9±8.21 vs. 74.0±8.03 mm Hg; p = 0.009) compared to participants without DR. There were also significant differences in age at diagnosis of DM and gender where participants with development of DR were younger at onset (23.5±5.39 vs. 25.2±5.52 years; p = 0.03) and the proportion of men was higher (65.0 vs. 50.6%; p = 0.03). No significant differences were found between the groups (DR vs. no DR) regarding the type of DM, (T1DM 65.0 vs. 68.0%; p = 0.64), the levels of ICA (48.0(0–1000) vs. 128(0–1000) Juvenile Diabetes Foundation (JDF) units; p = 0.40) or tobacco use (50.0 vs. 45.8%; p = 0.54). No significant differences were found between the groups (DR vs. no DR) regarding the levels of the adhesion molecules sE-selectin (10.4(7.64–12.5) vs. 9.33(6.80–12.2) ng/ml; p = 0.25), sICAM-1 (109(80.3–153) vs. 106(73.3–150) ng/ml; p = 0.93) or sVCAM-1 (490±154 vs. 455±157 ng/ml; p = 0.09).

Significant negative correlations were found between sICAM-1 and ICA (rs = -0.19; p = 0.002), and sVCAM-1 and ICA (rs = -0.13; p = 0.04). No correlation was found between sE-selectin and ICA. No correlation was found between the levels of ICA and age at diagnosis of DM.

In a logistic regression model with DR as the dependent variable and mean HbA1c, mean BMI, systolic BP, diastolic BP, gender, and age at DM diagnosis as independent variables, all lost statistical significance except mean HbA1c (Odds Ratio 1.04, 95% CI 1.02–1.07; p = 0.0001).

Participants with T1DM who had developed DR 8–10 years after diagnosis of DM had statistically significantly higher mean HbA1c (p<0.001), mean BMI (p = 0.019), systolic BP (p = 0.002) and diastolic BP (p = 0.003), but lower age at diagnosis of DM (p = 0.015) compared to participants without DR. The proportion of men was higher among those with T1DM and DR, as compared to no DR (p = 0.026). Regarding sE-selectin, sICAM-1, and sVCAM-1 in participants with T1DM no differences were observed between the groups with or without DR.

Among participants with T2DM, no statistically significant differences regarding mean HbA1c and clinical data were found between those with development of DR and without. Mean HbA1c was higher in the group with DR but did not reach statistical significance (p = 0.08). However, sE-selectin, but not sICAM-1 or sVCAM-1, was significantly higher in the group with T2DM and DR, as compared to no DR (11.8(9.97–12.6) vs. 9.43(5.85–12.7) ng/ml; p = 0.04).

Clinical and biochemical data for study participants with T1DM and T2DM with and without development of DR are presented in Table 1.

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Table 1. Clinical and biochemical data for study participants with type 1 and type 2 diabetes mellitus, aged 15–34 years at diagnosis of diabetes, with and without development of diabetic retinopathy 8–10 years after diagnosis of diabetes.

https://doi.org/10.1371/journal.pone.0304173.t001

Participants with T1DM had significantly lower mean BMI than participants with T2DM (p<0.001), but altogether no other differences in clinical data were found when comparing the two groups. Nevertheless, sICAM-1 was statistically higher in the group with T2DM (p = 0.001), whereas no statistically significant differences were found between T1DM and T2DM regarding sVCAM-1 (p = 0.07) and sE-selectin (p = 0.32). Clinical and biochemical data for study participants with T1DM and T2DM are presented in Table 2.

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Table 2. Comparison of clinical and biochemical data for study participants with type 1 and type 2 diabetes mellitus at diagnosis of diabetes and at follow-up 8–10 years after diagnosis of diabetes.

https://doi.org/10.1371/journal.pone.0304173.t002

Discussion

Since 1983, a nationwide population-based prospective study, registers the incidence of DM and its complications in the age group 15–34 years in Sweden. In the present study, we investigated the K-DISS baseline values of soluble adhesion molecules and subsequent development of DR 8–10 years after diagnosis of DM, in a cohort diagnosed with DM as young adults in 1987–88. The main finding of this study was that plasma levels of sE-selectin at diagnosis of DM were significantly higher in participants with T2DM who had developed DR 8–10 years after diagnosis of DM compared to participants with T2DM who had not. sE-selectin can therefore be a candidate for identification of T2DM patients at high risk of developing DR. Our research indicates that the levels of sE-selectin may serve as a predictive biomarker for the development of DR in patients with T2DM, similar to the results in the DCCT/EDIC regarding patients with T1DM [32]. Increased levels of sE-selectin have previously been shown to be associated with insulin resistance/hyperinsulinemia [44] which may support our results with significantly increased levels of sE-selectin, but not sICAM-1 and sVCAM-1, in the group with DR in T2DM.

Matsumoto et al. has determined sE-selectin, sICAM-1, and sVCAM-1 in participants with T2DM grouped by presence or absence of DR and reported significantly higher levels of all three adhesion molecules independent of HbA1c in participants with DR [19]. In our study, a predictive role for sICAM-1 and sVCAM-1 at diagnosis of DM regarding development of DR could not be identified neither for T1DM nor T2DM, which is in accordance with the findings in the DCCT/EDIC, where the expressions of sICAM-1 and sVCAM-1 could not predict initiation or progression of DR in T1DM [32]. On the other hand, a large study by the EURODIAB Prospective Complications Study group has shown positive associations with DR for both sE-selectin and sVCAM-1 in T1DM [25]. In the same study, a high correlation was found between sE-selectin and HbA1c indicating that sE-selectin expression on the endothelium was influenced by glycemic control. The inflammatory activity associated with T1DM has been shown to be partly induced by hyperglycemia through adhesion molecules and endothelial dysfunction [45]. To reduce the risk of developing DR in DM, strategies must focus on the improvement of endothelial function as well as control of conventional risk factors.

HbA1c is a well-known predictive biomarker for development of DR [10, 11, 13]. Prior research has demonstrated the impact of early glycemic control on prevention of DR and diabetic kidney disease in childhood-onset T1DM [46]. This study confirmed that suboptimal glycemic control over the course of the disease, measured as mean HbA1c, is a strong predictor for development of DR in T1DM. The prevalence of DR in the cohort was high, 31.7%, even though the participants were intensively treated and used self-glucose monitoring during the follow-up period. Patients with DM may develop microvascular complications despite reasonable glycemic control, indicating the importance of other risk factors. Altogether, we found that the clinical characteristics suboptimal glycemia during follow-up, higher mean BMI, higher systolic and diastolic BP, male gender, and younger age at DM diagnosis were associated with development of DR in T1DM, but not T2DM. However, in a multivariate analysis only mean HbA1c remained as a risk factor. A correct classification of DM is important in this age group. As previously shown, young patients with T2DM have a higher prevalence of severe DR, i.e., moderate or severe non-proliferative DR and proliferative DR, than young patients with T1DM [14]. Regularly performed dilated eye examinations in DM are needed according to treatment guidelines [47, 48].

In this study, higher mean BMI was significantly associated with the development of DR in T1DM and participants with T1DM had significantly lower BMI than participants with T2DM. The association between higher BMI and an increased risk of developing DR has previously been reported [12].

There is no clear gender difference in the development of DR. In this cohort of adolescents and young adults, male gender was associated with development of DR in T1DM. In the Wisconsin Epidemiologic Study of Diabetic Retinopathy XXII, being male was significantly associated with progression of DR in T1DM, independent of other risk factors [12]. However, a higher prevalence of DR in T1DM has been reported for adolescent girls compared to boys in an Australian study [49]. Among American youth with T2DM, males were at higher risk of developing DR compared to females [50], which could not be confirmed in our study. The difference between genders and the development of DR in prior research might depend on the age of onset of DM or hormonal differences during puberty. In the cohort, aged 15–34 years at diagnosis, younger age at diagnosis of T1DM was associated with development of DR. This is consistent with a study reporting higher risk of vascular complications in those living with DM during puberty, compared to young people developing DM after puberty [51]. Therefore, it is important to screen for early signs of DR and thereby identifying risk factors that can be addressed during adolescence.

Incident participants with T1DM in DISS have shown a significant decrease in the frequency of ICA, but not in the levels of ICA, with increasing age, particularly in men [43]. In accordance, this sub study did not show any correlation between the levels of ICA and age at diagnosis of T1DM. However, significant negative correlations were found between sICAM-1 and ICA, and between sVCAM-1 and ICA. On the contrary, other studies have shown a positive correlation [52] or no correlation [53] between sICAM-1 and ICA in patients with T1DM. Whether the adhesion molecules are independent of ICA status or not is still elusive and needs further investigations.

This prospective study has several strengths. It is a nationwide and population-based study with a well-defined cohort of young adults with DM and a long follow-up period of 8–10 years, making it possible to longitudinally identify development of microvascular complications. ICA were used to accurately classify between T1DM and T2DM. Furthermore, patients who developed nephropathy or concomitant nephropathy and DR during follow-up were excluded in order not to risk investigating patients with nephropathy caused by conditions unrelated to DM. Commercially available assays with high sensitivity and low variation were used.

The limitations of our study should also be mentioned. Only baseline levels of the adhesion molecules were measured for the study participants, and the results were consequently restricted to a single measurement of those. It is possible that some degradation may have occurred due to long storage time although the adhesion molecules measured have been shown to remain stable in stored specimens. The exclusion of study participants due to insufficient blood samples in the group with DR and the group without DR were 30% and 23%, respectively. The samples had been used in previous studies, and some of the tubes did no longer contain large enough blood volume for the tests to be conducted. The study focused on adolescents and young adults diagnosed with T1DM and T2DM. However, the majority of those who develop T2DM are diagnosed later in life. Therefore, a broader age range could impact the results. The length of the time interval between onset and diagnosis of T1DM and T2DM may differ and hence, the diabetes duration, with T2DM often having a longer asymptomatic period before diagnosis and therefore a higher risk of microvascular complications at diagnosis and time of inclusion in the study. Although this study has a small number of participants with onset of T2DM in adolescence and early adulthood (n = 83), the results are interesting, since the number of patients with T2DM is increasing globally with diagnosis being made at younger and younger ages.

The results of different published investigations are varying, indicating the potential presence of unidentified factors that may influence the levels of adhesion molecules observed in DR. Chronic inflammation is believed to play a role in the pathogenesis of DR, yet the precise mechanism remains unclear. Our findings do not explain the variation in results reported in prior research, but illustrate a possible association between adhesion molecules in endothelial activation and DR. Further research aiming at defining biomarkers able to identify patients at high risk of developing DR already at diagnosis of DM is essential. Non-invasive, accurate, and cost-effective biomarkers would be needed to help reducing the incidence and progression of DR. Until better biomarkers are available, we must adhere to current treatment guidelines. Enhanced screening for T2DM, improved management of DM and improved screening and treatment of DR have all contributed to a decline in both incidence and severity of DR. This underscores the importance of early intervention and efficient treatment, as target tissues appear to retain a memory of poor metabolic control, even many years later, currently known as the “legacy effect” [54].

In conclusion, there was a significant association between increased plasma levels of sE-selectin at diagnosis of T2DM and development of DR within 10 years. The clinical characteristics: suboptimal glycemia, higher BMI, higher systolic and diastolic BP, male gender, and younger age at DM diagnosis for young adults predicted development of DR in T1DM, but not T2DM.

The results from this study encourage further exploration in larger populations and with longer follow-up periods to uncover new biomarkers for early prediction of DR, facilitating tailored and timely interventions from diagnosis of DM for high-risk patients.

Acknowledgments

We would like to acknowledge Birgitte Ekholm and Pernilla Katra for excellent technical assistance in the research laboratory.

Members of the Diabetes Incidence Study in Sweden Group during collection of blood samples were Mona Landin-Olsson, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden (e-mail: mona.landin-olsson@med.lu.se), Hans J Arnqvist, Department of Endocrinology, Linköping University Hospital, Linköping, Sweden, Jan Bolinder, Department of Endocrinology, Metabolism, and Diabetes, Karolinska University Hospital, Huddinge, Karolinska Institutet, Stockholm, Sweden, Jan Östman, Department of Endocrinology, Metabolism, and Diabetes, Karolinska University Hospital, Huddinge, Karolinska Institutet, Stockholm, Sweden, Jan W Eriksson, Department of Public Health and Clinical Medicine, Epidemiology, Umeå University, Umeå, Sweden, and Lennarth Nyström, Department of Public Health and Clinical Medicine, Epidemiology, Umeå University, Umeå, Sweden.

References

  1. 1. Ludvigsson J. Increasing Incidence but Decreasing Awareness of Type 1 Diabetes in Sweden. Diabetes Care. 2017;40(10):e143–e4. pmid:28784725
  2. 2. Ogle GD, James S, Dabelea D, Pihoker C, Svennson J, Maniam J, et al. Global estimates of incidence of type 1 diabetes in children and adolescents: Results from the International Diabetes Federation Atlas, 10th edition. Diabetes Res Clin Pract. 2022;183:109083. pmid:34883188
  3. 3. Wu H, Patterson CC, Zhang X, Ghani RBA, Magliano DJ, Boyko EJ, et al. Worldwide estimates of incidence of type 2 diabetes in children and adolescents in 2021. Diabetes Res Clin Pract. 2022;185:109785. pmid:35189261
  4. 4. Yau JW, Rogers SL, Kawasaki R, Lamoureux EL, Kowalski JW, Bek T, et al. Global prevalence and major risk factors of diabetic retinopathy. Diabetes Care. 2012;35(3):556–64. pmid:22301125
  5. 5. Lee R, Wong TY, Sabanayagam C. Epidemiology of diabetic retinopathy, diabetic macular edema and related vision loss. Eye Vis (Lond). 2015;2:17. pmid:26605370
  6. 6. Dabelea D, Stafford JM, Mayer-Davis EJ, D’Agostino R Jr., Dolan L, Imperatore G, et al. Association of Type 1 Diabetes vs Type 2 Diabetes Diagnosed During Childhood and Adolescence With Complications During Teenage Years and Young Adulthood. JAMA. 2017;317(8):825–35. pmid:28245334
  7. 7. Porter M, Channa R, Wagner J, Prichett L, Liu TYA, Wolf RM. Prevalence of diabetic retinopathy in children and adolescents at an urban tertiary eye care center. Pediatr Diabetes. 2020;21(5):856–62. pmid:32410329
  8. 8. Downie E, Craig ME, Hing S, Cusumano J, Chan AK, Donaghue KC. Continued reduction in the prevalence of retinopathy in adolescents with type 1 diabetes: role of insulin therapy and glycemic control. Diabetes Care. 2011;34(11):2368–73. pmid:22025782
  9. 9. Bjornstad P, Drews KL, Caprio S, Gubitosi-Klug R, Nathan DM, Tesfaldet B, et al. Long-Term Complications in Youth-Onset Type 2 Diabetes. N Engl J Med. 2021;385(5):416–26. pmid:34320286
  10. 10. The Diabetes Control And Complications Trial Research Group. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med. 1993;329:977–86. pmid:8366922
  11. 11. Stratton IM, Kohner EM, Aldington SJ, Turner RC, Holman RR, Manley SE, et al. UKPDS 50: Risk factors for incidence and progression of retinopathy in Type II diabetes over 6 years from diagnosis. Diabetologia. 2001;44:156–63. pmid:11270671
  12. 12. Klein R, Knudtson MD, Lee KE, Gangnon R, Klein BE. The Wisconsin Epidemiologic Study of Diabetic Retinopathy: XXII the twenty-five-year progression of retinopathy in persons with type 1 diabetes. Ophthalmology. 2008;115(11):1859–68. pmid:19068374
  13. 13. Nordwall M, Fredriksson M, Ludvigsson J, Arnqvist HJ. Impact of Age of Onset, Puberty, and Glycemic Control Followed From Diagnosis on Incidence of Retinopathy in Type 1 Diabetes: The VISS Study. Diabetes Care. 2019;42(4):609–16. pmid:30705061
  14. 14. Henricsson M, Nyström L, Blohmé G, Östman J, Kullberg C, Svensson M, et al. The Incidence of Retinopathy 10 Years After Diagnosis in Young Adult People With Diabetes. Diabetes Care. 2003;26(2):349–54.
  15. 15. Hietala K, Harjutsalo V, Forsblom C, Summanen P, Groop PH, FinnDiane Study G. Age at onset and the risk of proliferative retinopathy in type 1 diabetes. Diabetes Care. 2010;33(6):1315–9. pmid:20185730
  16. 16. Hautala N, Hannula V, Palosaari T, Ebeling T, Falck A. Prevalence of diabetic retinopathy in young adults with type 1 diabetes since childhood: the Oulu cohort study of diabetic retinopathy. Acta Ophthalmol. 2014;92(8):749–52. pmid:24862935
  17. 17. Ferm ML, DeSalvo DJ, Prichett LM, Sickler JK, Wolf RM, Channa R. Clinical and Demographic Factors Associated With Diabetic Retinopathy Among Young Patients With Diabetes. JAMA Netw Open. 2021;4(9):e2126126. pmid:34570208
  18. 18. Today Study Group. Retinopathy in youth with type 2 diabetes participating in the TODAY clinical trial. Diabetes Care. 2013;36(6):1772–4. pmid:23704677
  19. 19. Matsumoto K, Sera Y, Ueki Y, Inukai G, Niiro E, Miyake S. Comparison of serum concentrations of soluble adhesion molecules in diabetic microangiopathy and macroangiopathy. Diabet Med. 2002;19(10):822–6. pmid:12358868
  20. 20. Goldberg RB. Cytokine and cytokine-like inflammation markers, endothelial dysfunction, and imbalanced coagulation in development of diabetes and its complications. J Clin Endocrinol Metab. 2009;94(9):3171–82. pmid:19509100
  21. 21. Morigi M, Angioletti S, Imberti B, Donadelli R, Micheletti G, Figliuzzi M, et al. Leucocyte-endothelial Interaction Is Augmented by High Glucose Concentrations and Hyperglycemia in a NF-kB-dependent Fashion. J Clin Invest. 1998;101(9):1905–15.
  22. 22. Heier M, Margeirsdottir HD, Brunborg C, Hanssen KF, Dahl-Jorgensen K, Seljeflot I. Inflammation in childhood type 1 diabetes; influence of glycemic control. Atherosclerosis. 2015;238(1):33–7. pmid:25437887
  23. 23. van Hecke MV, Dekker JM, Nijpels G, Moll AC, Heine RJ, Bouter LM, et al. Inflammation and endothelial dysfunction are associated with retinopathy: the Hoorn Study. Diabetologia. 2005;48(7):1300–6. pmid:15918015
  24. 24. Kern TS. Contributions of inflammatory processes to the development of the early stages of diabetic retinopathy. Exp Diabetes Res. 2007;2007:95103. pmid:18274606
  25. 25. Soedamah-Muthu SS, Chaturvedi N, Schalkwijk CG, Stehouwer CD, Ebeling P, Fuller JH, et al. Soluble vascular cell adhesion molecule-1 and soluble E-selectin are associated with micro- and macrovascular complications in Type 1 diabetic patients. J Diabetes Complications. 2006;20(3):188–95. pmid:16632240
  26. 26. Adamiec-Mroczek J, Oficjalska-Mlynczak J. Assessment of selected adhesion molecule and proinflammatory cytokine levels in the vitreous body of patients with type 2 diabetes—role of the inflammatory-immune process in the pathogenesis of proliferative diabetic retinopathy. Graefes Arch Clin Exp Ophthalmol. 2008;246(12):1665–70. pmid:18682976
  27. 27. Sharma S, Purohit S, Sharma A, Hopkins D, Steed L, Bode B, et al. Elevated Serum Levels of Soluble TNF Receptors and Adhesion Molecules Are Associated with Diabetic Retinopathy in Patients with Type-1 Diabetes. Mediators Inflamm. 2015;2015:279393. pmid:26339132
  28. 28. Nowak M, Wielkoszynski T, Marek B, Kos-Kudla B, Swietochowska E, Sieminska L, et al. Blood serum levels of vascular cell adhesion molecule (sVCAM-1), intercellular adhesion molecule (sICAM-1) and endothelial leucocyte adhesion molecule-1 (ELAM-1) in diabetic retinopathy. Clin Exp Med. 2008;8(3):159–64. pmid:18791689
  29. 29. Blum A, Pastukh N, Socea D, Jabaly H. Levels of adhesion molecules in peripheral blood correlat with stages of diabetic retinopathy and may serve as bio markers for microvascular complications. Cytokine. 2018;106:76–9. pmid:29133026
  30. 30. Yao Y, Du J, Li R, Zhao L, Luo N, Zhai JY, et al. Association between ICAM-1 level and diabetic retinopathy: a review and meta-analysis. Postgrad Med J. 2019;95(1121):162–8. pmid:31109934
  31. 31. Muni RH, Kohly RP, Lee EQ, Manson JE, Semba RD, Schaumberg DA. Prospective study of inflammatory biomarkers and risk of diabetic retinopathy in the diabetes control and complications trial. JAMA Ophthalmol. 2013;131(4):514–21. pmid:23392399
  32. 32. Rajab HA, Baker NL, Hunt KJ, Klein R, Cleary PA, Lachin J, et al. The predictive role of markers of Inflammation and endothelial dysfunction on the course of diabetic retinopathy in type 1 diabetes. J Diabetes Complications. 2015;29(1):108–14. pmid:25441222
  33. 33. Boulbou MS, Koukoulis GN, Petinaki EA, Germenis A, Gourgoulianis KI. Soluble adhesion molecules are not involved in the development of retinopathy in type 2 diabetic patients. Acta Diabetol. 2004;41(3):118–22. pmid:15666579
  34. 34. Ersanli D, Top C, Oncul O, Aydin A, Terekeci H. Relationship between serum soluble E-selectin levels and development of diabetic retinopathy in patients with type 2 diabetes. Scand J Clin Lab Invest. 2007;67(5):474–9. pmid:17763183
  35. 35. Spijkerman AM, Gall MA, Tarnow L, Twisk JW, Lauritzen E, Lund-Andersen H, et al. Endothelial dysfunction and low-grade inflammation and the progression of retinopathy in Type 2 diabetes. Diabet Med. 2007;24(9):969–76. pmid:17593241
  36. 36. Ostman J, Arnqvist H, Blohmé G, Lithner F, Littorin B, Nyström L, et al. Epidemiology of diabetes mellitus in Sweden. Results of the first year of a prospective study in the population age group 15–34 years. Acta Med Scand. 1986;220(5):437–45. pmid:3812028
  37. 37. Svensson M, Sundkvist G, Arnqvist HJ, Björk E, Blohmé G, Bolinder J, et al. Signs of Nephropathy May Occur Early in Young Adults With Diabetes Despite Modern Diabetes Management. Diabetes Care. 2003;26(10):2903–9.
  38. 38. Svensson MK, Tyrberg M, Nystrom L, Arnqvist HJ, Bolinder J, Ostman J, et al. The risk for diabetic nephropathy is low in young adults in a 17-year follow-up from the Diabetes Incidence Study in Sweden (DISS). Older age and higher BMI at diabetes onset can be important risk factors. Diabetes Metab Res Rev. 2015;31(2):138–46. pmid:25044633
  39. 39. Diabetes mellitus. Report of a WHO Study Group. World Health Organ Tech Rep Ser. 1985;727:1–113.
  40. 40. Klein R, Klein BE, Magli YL, Brothers RJ, Meuer SM, Moss SE, et al. An alternative method of grading diabetic retinopathy. Ophthalmology. 1986;93(9):1183–7. pmid:3101021
  41. 41. Madsen OD, Olsson ML, Bille G, Sundkvist G, Lernmark A, Dahlqvist G, et al. A two-colour immunofluorescence test with a monoclonal human proinsulin antibody improves the assay for islet cell antibodies. Diabetologia. 1986;29(2):115–8. pmid:3516766
  42. 42. Landin-Olsson M, Sundkvist G, Lernmark Å. Prolonged incubation in the two-colour immunoflourescence test increases the prevalence and titres of islet cell antibodies in Type 1 diabetes mellitus. Diabetologia. 1987;30:327–32.
  43. 43. Landin-Olsson M, Karlsson FA, Lernmark Å, Sundkvist G, Group TDISiS. Islet Cell and Thyrogastric Antibodies in 633 Consecutive 15- to 34-Yr-Old Patients in the Diabetes Incidence Study in Sweden. Diabetes. 1992;41(8):1022–7. pmid:1628762
  44. 44. Matsumoto K, Miyake S, Yano M, Ueki Y, Tominaga Y. High serum concentrations of soluble E-selectin in patients with impaired glucose tolerance with hyperinsulinemia. Atherosclerosis. 2000;152(2):415–20. pmid:10998470
  45. 45. Schram MT, Chaturvedi N, Schalkwijk C, Giorgino F, Ebeling P, Fuller JH, et al. Vascular risk factors and markers of endothelial function as determinants of inflammatory markers in type 1 diabetes: the EURODIAB Prospective Complications Study. Diabetes Care. 2003;26(7):2165–73. pmid:12832330
  46. 46. Svensson M, Eriksson JW, Dahlquist G. Early glycemic control, age at onset, and development of microvascular complications in childhood-onset type 1 diabetes: a population-based study in northern Sweden. Diabetes Care. 2004;27(4):955–62. pmid:15047655
  47. 47. Bjornstad P, Dart A, Donaghue KC, Dost A, Feldman EL, Tan GS, et al. ISPAD Clinical Practice Consensus Guidelines 2022: Microvascular and macrovascular complications in children and adolescents with diabetes. Pediatr Diabetes. 2022;23(8):1432–50. pmid:36537531
  48. 48. Elsayed NA, Aleppo G, Bannuru RR, Bruemmer D, Collins BS, Ekhlaspour L, et al. 12. Retinopathy, Neuropathy, and Foot Care: Standards of Care in Diabetes—2024. Diabetes Care. 2024;47(Supplement_1):S231–S43. pmid:38078577
  49. 49. Benitez-Aguirre P, Craig ME, Cass HG, Sugden CJ, Jenkins AJ, Wang JJ, et al. Sex differences in retinal microvasculature through puberty in type 1 diabetes: are girls at greater risk of diabetic microvascular complications? Invest Ophthalmol Vis Sci. 2014;56(1):571–7. pmid:25477322
  50. 50. Wang SY, Andrews CA, Herman WH, Gardner TW, Stein JD. Incidence and Risk Factors for Developing Diabetic Retinopathy among Youths with Type 1 or Type 2 Diabetes throughout the United States. Ophthalmology. 2017;124(4):424–30. pmid:27914837
  51. 51. Cho YH, Craig ME, Donaghue KC. Puberty as an accelerator for diabetes complications. Pediatr Diabetes. 2014;15(1):18–26. pmid:24443957
  52. 52. Myśliwiec J, Kretowski A, Kinalski M, Kinalska I. CD11a expression and soluble ICAM-1 levels in peripheral blood in high-risk and overt type 1 diabetes subjects. Immunol Lett. 1999;70(1):69–72. pmid:10541054
  53. 53. Lampeter ER, Kishimoto TK, Rothlein R, Mainolfi EA, Bertrams J, Kolb H, et al. Elevated levels of circulating adhesion molecules in IDDM patients and in subjects at risk for IDDM. Diabetes. 1992;41(12):1668–71. pmid:1280239
  54. 54. Reddy MA, Zhang E, Natarajan R. Epigenetic mechanisms in diabetic complications and metabolic memory. Diabetologia. 2015;58(3):443–55. pmid:25481708