Relationship of Central Corneal Thickness and Central Corneal Epithelial Thickness with Anthropoemetric and Biochemical Data in Individuals with Impaired Glucose Metabolism

doi:10.21203/rs.3.rs-3239513/v1

Background

Measure central corneal thickness (CCT) and central corneal epithelial thickness (CCET) with anterior segment-optical coherence tomography (AS-OCT) in individuals with impaired glucose metabolism and to analyze, the effect of impaired glucose metabolism on the cornea.

Methods

140 eyes of 70 participants, including 20 healthy controls, 17 insulin resistant, and 33 prediabetic, were evaluated by AS-OCT. Glucose metabolism was examined using a 2-hour 75 g oral glucose tolerance test and glycated haemoglobin A1c (HbA1c). Anthropoemetric measurements, physical examinations, and blood pressure were recorded of all participants. The biochemical parameters were studied.

Results

The mean age of the participants was 37.93±12.30 years, and the mean HbA1c was 5.50±0.38%. CCET measurements were significantly different and higher in the prediabetic group (p<0.01). A significant positive correlation was found between both CCETR and CCETL and age, HbA1c, and fasting plasma glucose (p<0.05). There was found a significant positive correlation was found between CCETR and total cholesterol, triglyceride, and low-density lipoprotein (p<0.05). Anthropoemetric parameters were significantly different in prediabetics (p˂0.001 and p˂0.05). There was a significant negative correlation between body fat percentage and CCT (p˂0.05). CCET showed a significant positive correlation with neck circumference (p<0.05).

Conclusions

It may be suggested that impaired metabolic processes during prediabetes may affect CCET. We believe that prediabetes detection should not be limited to HbA1c and OGTT; A multifactorial algorithm could be developed. AS-OCT may be an easily accessible and useful tool for the early diagnosis of prediabetes.

Central corneal thickness

central corneal epithelial thickness

impaired glucose metabolism

optical coherence tomography

oral glucose tolerance test

prediabetes.

Type 2 diabetes mellitus (T2D) is a metabolic disease characterized by hyperglycemia resulting from insulin resistance or insulin deficiency [1,2]. On the other hand, prediabetes, which is considered the precursor of diabetes, is an intermediate metabolic state between normal glucose metabolism and diabetes. The risk of developing T2D in prediabetes is up to 70% [3]. The burden of prediabetes on a global scale is quite high; it is estimated that it currently affects 373 million people, and this number will reach 587 million in 2045 [4,5].

Patients suffering from T2D are at risk of developing classic microvascular complications such as retinopathy, neuropathy, and nephropathy which are major health problems. Chronic hyperglycemia and induced glucotoxicity increase inflammation resulting in microvascular damage to the retina. As a result, microangiopathy progresses and results in diabetic retinopathy (DR). DR is one of the most common causes of vision loss, especially in working-age populations globally [6].

Duration of diabetes, glycemic level, hypertension, hyperlipidemia, nephropathy, and neuropathy are powerful risk factors for the development and severity of retinopathy [7-11]. Although controlling these risk factors is important for the prevention of retinopathy, its development or progression rate is difficult to predict. Although good glycemic control reduces the risk of developing retinopathy, it can still develop despite a good glycemic control [12].

Diabetic neuropathy, which is a microvascular complication, occurs in the prediabetes period before hyperglycemia is evident [13,14]. Contrary to this situation, it remains unclear when DR started. However, to examine the pathogenesis and natural course of diabetic microangiopathy, as well as the effects of probable therapeutic treatments, it is necessary to know if there is an effect in the period of insulin resistance and prediabetes [15-18].

The duration of diabetes is also associated with increased corneal thickness [19-21]. It has been suggested that this increase is due to hyperglycemia in the tissue and the formation and deposition of advanced glycation end products (AGEs). Although changes that may be related to the corneal epithelium have been studied in T2D, no studies have been reported in prediabetes [21].

The effect of T2D on the retina has been well studied, but its effect on the cornea is not well known, also the effect of glycemia on central corneal thickness (CCT), central corneal epithelial thickness (CCET) and especially in prediabetes before the development of overt diabetes, has not been well studied. Therefore, it may also be important to understand the impact of glycemia on the anterior segment of the eye during prediabetes. Our aim in this study is to measure CCET and CCT noninvasively and also to examine their relationship with biochemical parameters in individuals with prediabetes and insulin resistance compared to healthy controls.

70 participants and 140 eyes who applied to the internal medicine outpatient clinics of the Istanbul Medipol University Vatan Health Application and Research Center were included in the study and were evaluated between 20.02.2022 and 20.04.22. Participants in this cross-sectional and prospective study were 20 healthy controls (HC), 17 insulin resistance (IR) and 33 prediabetic individuals. The age range of the individuals included in the study was 21-62 and the gender distribution consisted of 42 females and 28 males (Table 1). The prediabetes group was formed from those who met the American Diabetes Association (ADA) prediabetes diagnostic criteria. For the diagnosis insulin resistance, the homeostatic model of assessment-insulin resistance (HOMA-IR) formula [ fasting insulin level (µU/ml) x fasting glucose level (mg/dl) / 405] was used and those with HOMA-IR ≥ 2.7 were included in the study. Diagnostic criteria for T2D and prediabetes are based on the criteria of the ADA and the European Diabetes Working Association (EASD) [22].

Patients with a history of diabetes, those who underwent eye surgery, uveitis, glaucoma, dry eye disease, contact lens use, those who used growth factors and steroids, those who received treatment for hypertension and hyperlipidemia, those who were pregnant and those who used antibiotics in the last month were not included in the study. Furthermore, those who had a history of myocardial infarction, peripheral artery disease, stroke, or a chronic disease, major surgery 4 weeks before participating in the study, and during the follow-up period were not included in the study.

Clinical information

The participant's anamnesis was performed in the outpatient clinic and detailed physical examinations were performed. Body mass index (BMI) and waist/hip ratio (WHR) were measured during the examination. When standing, waist circumference was measured from the middle of the distance between the edge of the lower rib and the crista iliaca, and the hip was measured from the widest part of the hip. The waist/hip ratio was calculated in this way. The WHR values are considered as <1 cm for males and <0.8 cm for females. Neck circumference (NC) was measured from the lower part of the prominentia laryngea with a tape measure. Body fat percentage (BFP) was measured with a Tanita MC-780MA model. Systolic (SBP) and diastolic blood pressures (DBP) were measured (Erka Perfect Aneroid 201 001 02 manual). The initial appearance (phase I) of the Korotkoff voice was used to describe systolic blood pressure and its disappearance (phase V) diastolic blood pressure. Hypertension was described as SBP 140 ≥ mmHg, DBP ≥ 90 mmHg.

Evaluation of retinopathy

In ophthalmological examination; the best visual acuities, corrected by Snellen chart, were obtained in anamnesis and standard illumination. Before dilating the pupil, an anterior segment examination was performed with a slit lamp (Topcon SL-7F 2003, Japan) for corneal diseases, rubeosis iridis, lens opacification. After dilating the pupil, vitreous lesions and other possible diseases were also evaluated. Then, stereoscopic fundus examination was performed to investigate possible findings of the posterior segment such as diabetic retinopathy, diabetic maculopathy, atherosclerosis, as well as optic neuropathy, optic atrophy, and chorioretinitis scar. Fundus photography and FFA were used in necessary cases. At the end of the examination, anterior segment OCT (AS-OCT) scans were obtained.

AS-OCT measurements of corneal epithelial thickness

Optical coherence tomography is a non-contact, high-resolution cross-sectional ultrasound technology to evaluate structures within the eye. The OCT device that we used to evaluate the anterior segment and the cornea in this research was Revo FC (software version 11.0.4, Optopol Tech, Poland). Revo FC is a new generation multipurpose device that can be used for both anterior and posterior segments of the eye. The topography module of the device provides axial, epithelium, and corneal thickness maps. It uses 850nm SLE diod and scans 80000 measurements per second with an overall scan depth of 2.4 mm / ~5 mm in full range mode [23]. Epithelial maps with 8mm diameter are automatically generated by the built-in software. [24]. All measurements were performed and examined by an ophthalmologist (GD).

Laboratory analysis

Blood and urine samples of all participants were collected after at least 10 hours of fasting overnight. Blood samples were allocated to 8.5 ml vacuum tubes (Becton Dickinson). Glycated haemoglobin (HbA1c) samples were taken in 2 ml tubes containing EDTA. The samples were stored at -80 °C until analysis. HbA1c concentration was studied with boronate affinity technology (Quo-Lab®, EKF Diagnostics PLC, Cardiff, UK) and expressed as a percentage according to the National Glycohemoglobin Standardization Program (NGSP). Plasma glucose was studied using the glucose oxidase method. Impaired fasting glucose (IFG) and/or impaired glucose tolerance (IGT) were assigned a standard 2-hour 75 g glucose oral glucose tolerance test (OGTT). Insulin fasting level was measured with Cobas e411 and the C-peptide fasting level was analyzed with ADVIA Centaur XP (Siemens). The formula [fasting insulin level(µU/ml) x fasting glucose level(mg/dl)/405] was used to detect insulin resistance in the homeostatic model of assessment-insulin resistance (HOMA-IR). Fasting plasma glucose (FPG), triglyceride (TG), total cholesterol (T col), high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c), creatinine were studied with the Chemical Systems (Ortho Clinical Diagnostics) device. Albuminuria was tested using an I-Chroma reader device (Boditech). Creatinine clearance (glomerular filtration rate) (GFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula.

Statistical analysis

In descriptive statistics, numbers and percentages were used for categorical variables, mean ± standard deviation and median values (minimum-maximum) were used for numerical variables. The conformity of the variables to the normal distribution was examined using the one-sample Kolmogorov-Smirnov test. The Kruskal-Wallis test was applied to the nonnormally distributed variables to understand the difference between independent groups. A one-way ANOVA test was applied to normally distributed variables to understand the difference between independent groups. The post-hoc test Tukey, Dunnett’s and Tamhane’s T2 tests were applied according to the homogeneous distribution of the variance test. The chi-square test (X²) was applied to categorical nominal variables for comparison analysis between two independent groups. The Spearman analysis was performed for correlation. The level of statistical significance was taken as p<0.05 and the analysis was performed using SPSS V22.0 statistical software (SPSS, Inc. USA).

Distribution of study participants; consisted of 70 individuals and 140 eyes, HC 20 (28.5%), IR 17 (24.3%), and prediabetes 33 (47.2%). The genders of the participants were 28 men, 42 women, the mean age was 37.93±12.30, and the mean HbA1c was 5.50±0.38 %. CCTR (right) was determined as 535±35 μm, CCTL (left) 530±53 μm, CCETR (right) 60.8±5.7 μm and CCETL (left) 61.0±5.7 μm. Details of demographic and biochemical parameters of all participants were provided (Table 1). Age, 2-hour post load plasma glucose (2-h PPG), IR, blood pressure, NC, LDL-c, TG, albuminuria, alanine transaminase (ALT), CCTL, CCETR and CCETL did not show normal distribution, on the other hand, BMI, WHR, BFP, HbA1c, fasting insulin and CCTR showed normal distribution. It is given in Table 1 shows whether other parameters conform to the normal distribution (p<0.05). There was no difference between the sexes in terms of corneal parameters when the chi-square test was applied (CCTR p=0.045, CCTL p=0.555, CCETR p=0.425 and CCETL p=0.627).

The mean age of the prediabetes group was older advanced and significantly different from the other groups (p<0.01) (Table 2). BMI, WHR, NC, and BFP levels were found to be significantly different in prediabetics (p˂0.001) and p˂0.05) (Table 2) (Table 3). There was a significant negative correlation between BMI and CCTL and between BFP and bilateral CCT (p˂0.05). There was a significant positive correlation between CCET and NC (p˂0.05) (Table 4). SBP was significantly different from the other two groups compared to the control group (p<0.05) (Table 2). There was a significant negative correlation between CCTL and SBP (p<0.05) (Table 4).

FPG, TG, LDL-c and ALT levels were higher and significantly different in the prediabetes group (p<0.01). CCTL was found to be significantly higher in the control group (p<0.01). CCETR and CCETL were significantly different and higher in the prediabetes group (p<0.01). Hb A1c, fasting insulin, fasting C-peptide, T-col and eGFR levels were significantly different in the prediabetes group (p<0.01). In addition, spot creatinuria was found to be significantly different in the prediabetes group (p<0.05) (Table2) (Table 3).

In the correlation analysis, there was a significant positive correlation between CCETR and age, HbA1c and FPG (p<0.001). A significant positive correlation was found between CCETL and age, HbA1c, and FPG (p<0.05). There was a significant positive correlation between CCETR and T-col, TG, and LDL-c (p<0.05). There was a positive correlation between CCETL and TG, and a significant negative correlation between HDL-c (p<0.05). FPG value was negatively correlated with bilateral CCT (p<0.05) (Table 4).

İn some studies, it has been suggested that other complications of diabetes, especially DR, also start in the period of prediabetes. In these studies, the prevalence of DR has been reported to vary between 6% and 8% in prediabetics [5,18,25,26]. Because the corneal epithelium is avascular, it does not take glucose directly from the blood, but instead from the aqueous humor through the transcornea. In diabetes, the corneal epithelium is exposed to hyperglycemia, and severe inflammation and oxidative stress caused by chronic hyperglycemia in other tissues also occur in the corneal epithelium. It Metabolic disturbances have also been suggested to increase the risk of corneal epithelial damage, poor healing, and neurotrophic keratitis. Increased thickness and thus relative stiffness of the cornea can result in incorrectly high measurement of intraocular pressure [21,27-29].

The corneal epithelium, the first barrier that protects the eye against external aggressors, functions as an innate immune defense. Disruption of this barrier can predispose the cornea to infection and interfere with the eye's refractive abilities. Patients with diabetic keratopathy face primarily problems caused by the inability of the corneal epithelium to repair damage to the cornea and deterioration of tight barrier function [30,31]. CCT has been reported to be approximately 540-560 µm in healthy people, and it has been emphasized that it increases by 10-30 µm in patients with T2D. Duration of diabetes has been associated with increased corneal thickness [19-21,28,29]. The corneal epithelium is a stratified, nonkeratinized layer with a thickness of 48–53μm in healthy eyes, which has previously been shown to be moldable. It has an asymmetrical thickness profile, being slightly thicker inferiorly and nasally [32,33]. In a study conducted in well-controlled patients with T2D without retinopathy, it was emphasized that CET was increased, and this may be important in the early detection of DR [34].

In our data set in which we measured the CCT and CCET of prediabetics, the CCT right eye (CCTR) of prediabetics was 529±36 µm and CCT left eye (CCTL) was 520±67 µm. In addition, CCET of healthy people is approximately 50 µm and as we know, this is the first study measuring CCET of prediabetics [21]. In this study, CCETL 60.5±4.6 µm and CCETR 59.8±4.5 µm were found to be significantly higher than the other two groups. Based on these data, it can be suggested that CCET actually start to increase in the prediabetic period. Although information on the increase in corneal epithelial thickness in patients with T2D has been shared in some previous studies, so far there is no information in the literature that we can make this comparison in prediabetes. There is only one study in the literature that examines retina in prediabetes, suggesting that macular thickness decreases in prediabetics [15].

In our study, we found that the age of the prediabetes group was older than of the HC and IR groups (age: 47.67±7.24 years). The mean age of our prediabetes cohort was in parallel with that those reported in other series [18]. Determining an age cut-off point in a risk analysis scoring study for the early detection of prediabetes may yield very useful results for screening. In this way, proactive prevention of retinopathy development can be realized. As mentioned above, it has been suggested that the duration of diabetes is associated with an increase in corneal thickness in patients with T2D. Therefore, the effects of impaired glucose metabolism in prediabetics on the cornea during their stay in prediabetes may also be the subject of research (28,35). On the other hand, one explanation for the thicker central corneal thickness in the HC group compared to prediabetics may be due to the thickening beginning at the corneal epithelial level, and therefore CCET is higher in prediabetics. It may also be caused by the function of the corneal stroma to ensure the quality of corneal refraction in HC by providing electrolyte and water exchange with the endothelium [21,35-37].

In addition to the association of the duration of diabetes with increased corneal thickness, it has been suggested that increased glucose levels and the formation and accumulation of advanced glycation end products (AGEs) in the tissue may also be the reason [20,27]. Hyperglycemia and increased metabolic parameters in patients with T2D have been suggested to decrease Na+/K+-ATPase activity by causing oxidative stress [28,37]. There is information that this may result in thickening of the corneal basement membrane in diabetes [21,27]. Higher HbA1c values among individuals with prediabetes have been claimed to be associated with twice the relative risk for DR [18]. In our study, as expected the values of FPG and HbA1c values were higher in prediabetics compared to the other two groups. Furthermore, the levels of TG, Tcol, LDL-c, fasting insulin, and fasting C-peptide levels were significantly different and higher. CCETR and CCETL were found to increase in our prediabetes cohort in which all glycemic and lipemic parameters were found to be higher than in the HC group. These data support the hypothesis that impaired metabolic parameters during prediabetes affect the corneal epithelium, leading to thickening.

Hyperglycemia alters the expression of growth factors and mediators secreted by corneal epithelial cells, leading to acyclic deterioration in cell growth, emigration, and unity [31,38]. Transparency and homeostasis are largely maintained by the epithelium, and rapid regeneration and healing of the epithelial surface in case of injury or infection is essential. Diabetes may increase susceptibility to spontaneous corneal trauma, including epithelial erosions and ulcerations [20]. In our study, we found a significant positive correlation of CCET with age, FPG, HbA1c, T-col, TG and LDL-c. This suggests that deterioration in metabolic processes begins during prediabetes and although the early effects on corneal health have not been well investigated, it is likely that the structure and function of the entire cornea are altered before the diagnosis of diabetes, given the continuum of diseases seen in other sections of the body [21]. Maintaining normoglycemic levels should be the primary goal of corneal health.

Small-sized population-based studies have also not found a relationship between obesity and corneal thickness [39,40]. However, a study reported significant associations between corneal thickness and body weight, BMI, FPG and PPG at 2 hours [41]. In our study, the anthropoemetric data of prediabetics were found to be significantly different and higher than those of the other groups. WHR and NC showed a significant positive correlation with CCET. On the other hand, BMI, and BF% showed a significant negative correlation with CCT. There were also significant correlations between obesity parameters and glycemic and lipidemic parameters of prediabetics. Interestingly, CCT and CCET correlated differently, with CCT showing a negative correlation and CCET a positive correlation. This paradox, which we tried to explain above, may be explained by the decrease in corneal stroma/endothelial cell density in patients with T2D, and this can lead to changes such as pleomorphism/polymegatism [21]. The correlation of obesity and prediabetes glycemic parameters with corneal epithelial thickness in our data is compatible with the metabolic disease corneal damage relationship model.

Most of the time patients with T2D are admitted to ophthalmologic clinics only after the visible signs and symptoms of diabetic retinopathy. Therefore, early detection of diabetes in the early prediabetic period is important in terms of preventing the disease and developing treatment modalities. The diabetes and ophthalmology societies recommend a comprehensive eye examination at the time of diagnosis of T2D, five years after diagnosis of type 1 diabetes ellitus, and annually thereafter [42-44]. There are no specific guidelines for patients with prediabetes or obesity. Research on the eye in T2D patients has been done on the retina in general, and more studies focusing on the cornea, especially in prediabetics, should be encouraged.

In studies of T2D, microalbuminuria and decreased renal function have been found to be associated with DR [45]. In our study, proteinuria and decreased GFR, which are indicators of nephropathy, were studied with CCET/CCT and no correlation was found between them.

The limitation of this study is the lack of neuropathy questions. Furthermore, due to the small number of participants in the insulin resistance group, adequate comparisons could not be made.

The most important modifiable risk factors for preventing the progression of diabetic retinopathy and reducing the risk of vision loss are hyperglycemic and hypertensive conditions [8]. Although studies have encouraged the monitoring and strong control of HbA1c even before the diagnosis of diabetes, we do not think that this parameter alone is sufficient for both diagnosis and treatment [18]. A screening algorithm should be made in which OGTT and HbA1c are used in combination, taking into account age, sex, obesity, gestational diabetes, hyperlipidemia, hypertension, smoking, and other similar risk factors. Although the American Diabetes Association recommends testing for HbA1c all patients over 45 years of age and overweight adults of all ages, it is obvious that this is not enough [44]. In addition, biomarker studies for early diagnosis should be emphasized. In addition to the access of family physicians and internal medicine specialists to these tests, the access of ophthalmologists should also be ensured. In this way, it may be possible to find out more patients in the previous period. A mobile cell phone risk assessment app can be performed using anthropometric data, noninvasive eye examination parameters, and metabolic biomarkers. In today's world, such applications are rapidly and widely used in outpatient clinics and make great contributions in accordance with the purpose.

In conclusion, hyperglycemia, dyslipidemia, age, and duration of diabetes are important risk factors for diabetic retinopathy in, but these parameters may also be important in prediabetics. It may be suggested that deterioration in metabolic processes starts during prediabetes, and this may have an effect on CCET. We believe that according to these findings, the duration of prediabetes should also be considered in studies. On the other hand, obesity is found to be a risk factor that increases CCET in prediabetics. Based on all of these findings, we believe that prediabetes screening should not be limited to HbA1c and OGTT alone; we believe that a multifactorial algorithmic risk scale may be useful. Finally, we believe that family physicians, internal medicine, and ophthalmology specialists should play an active role in the early recognition of prediabetes and in the early diagnosis and treatment of other complications, especially diabetic retinopathy. Equipping these specialties with sufficient knowledge, experience, and equipment for early diagnosis is the most crucial point of the issue.

In prediabetes, AS-OCT can be a non-invasive, easily accessible, and useful tool for the early diagnosis of ocular changes. More research is needed to determine the possible effects of prediabetes on corneal health. Additionally, it would be beneficial to encourage researches on the cornea and anterior segment in prediabetes. On the other hand, identifying and developing potential therapeutic agents that can accelerate corneal reepithelialisation or protect against oxidative stress during prediabetes may also be crucial.

Advanced glycation end products

AGEs

Alanine Transaminase

ALT

American Diabetes Association

ADA

Anterior Segment-Optical Coherence Tomography

AS-OCT

Body Fat Percentage

BFP

Body Mass Index

BMI

Central Corneal Epithelial Thickness

CCET

Central Corneal Epithelial Thickness Left

CCETL

Central Corneal Epithelial Thickness Right

CCETR

Central Corneal Thickness

CCT

Central Corneal Thickness Left

CCTL

Central Corneal Thickness Right

CCTR

Chronic Kidney Disease Epidemiology Collaboration

CKD-EPI

Diabetic Retinopathy

DR

Diastolic Blood Pressures

DBP

European Diabetes Working Association

EASD

Fasting Plasma Glucose

FPG

Glomerular Filtration Rate

GFR

Glycated Haemoglobin A1c

HbA1c

Healthy Controls

HC

High-Density Lipoprotein Cholesterol

HDL-c

Homeostatic Model Of Assessment-Insulin Resistance

HOMA-IR

Impaired Fasting Glucose

IFG

Impaired Glucose Tolerance

IGT

Insulin Resistance

IR

Low-Density Lipoprotein Cholesterol

LDL-c

National Glycohemoglobin Standardization Program

NGSP

Neck Circumference

NC

Oral Glucose Tolerance Test

OGTT

Systolic Blood Pressures

SBP

Triglyceride

TG

Total Cholesterol

T col

Type 2 Diabetes Mellitus

T2D

Waist/Hip Ratio

WHR

2-hour Post Load Plasma Glucose

2-h PPG

Acknowledgements

We would like to thank the laboratory supervisor biologist Emel Altınkaynak, our assistants Selcan Unar, Nurgül Aydıner and optician technician Muhlise Serra Uyar for their contribution to the preparation of this study.

Authors’ Contributions

İ.B. brought up the idea of the study and drafted the project. Also, İ.B. ensured the selection of participants, their physical examination, anthropometric measurements, and the collection of study materials (blood, urine). İ.B. analyzed physical examination and biochemical data in the study. In addition, İ.B. performed the calculation and analysis of the statistical data of the article. G.D. performed ophthalmologic examinations and interpreted data provided by anterior segment optical coherence tomography. The writing of the article and the analysis of the data to be jointly decided were made by both authors.

Funding Sources

This research did not receive specific grants from funding agencies in the public, commercial or non-profit sectors.

Data Availability Statement

All data obtained in this study are included in this published article. More questions can be directed to the corresponding author.
Ethics approval and consent to participate

Ethical approval (Decision No. E-10840098-772.02-1216) was obtained from the Istanbul Medipol University Non-Interventional Clinical Research Ethics Committee to conduct the study. The purpose of the study was explained in detail to the participant’s, informed consent was obtained from the participants to conduct and record interviews, by informing them that participation was voluntary, their right to privacy and confidentiality would be reserved, and they could withdraw from the study at any time. The principles of the Declaration of Helsinki were complied with in the study.

Consent for publication

Written consent for publication was obtained from all participants in order to participate in the research and to publish the data in an article.

Competing interests

The authors declare that they have no conflicts of interest.

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Table 1. Basic characteristics of the participants enrolled in study
Group		Healthy control	Insulin resistant	Prediabetes	All participants	P value
Number	n (%)	20 (28.5)	17 (24.3)	33 (47.2)	70
Age	(year)	28.1±8	30.59±9	47.67±7.24	37.9 3±12	0.002*
Female sex,	n (%)	16 (38.1%)	12 (28.5%)	14 (33.4%)	42F / 28M
BMI	(kg/m²)	21.7±2.8	25.4±4.6	29.1±3.8	26.1±.4.8	0.200
WHR	(cm)	0.78±0.12	0.82±0.09	0.90±0.06	0.84±0.1	0.200
NC	(cm)	34.7±2.3	37.5±4.2	42.5±3.3	39.1±4.7	0.025*
BFP	(%)	22.2±6.6	27.3±6.2	26.9±6.8	25.7±6.9	0.200
SBP	(mmHg)	108±7	117±5	119±8	116±8	0.001*
DBP	(mmHg)	77±4	88±1	80±2	79±3	0.001*
HbA1c	(%)	5.25±0.21	5.25±0.3	5.78±0.31	5.5±0.38	0.200
FPG	(mmol/L)	5.13±0.35	5.38±0.36	5.87±0.55	5.52±0.56	0.056
2h PPG	(mmol/L)	6.61±0.1	6.17±0.65	6.60±1.69	6.54±1.57	0.005*
FI	(but/mL)	8.13±3.9	17.07±4.6	13.82±6.61	12.9±6.3	0.200
IR		1.8±0.9	4.05±1.1	3.87±2.7	3.34±2.2	0.009*
FC-p	(ng/mL)	1.8±0.5	2.8±0.6	2.7±0.8	2.5±0.8	0.200
T col	(mmol/L)	4.29±.0.87	4.76±0.34	5.52±1.08	4.93±1.09	0.200
TG	(mmol/L)	0.74±0.2	1.29±0.2	1.44±0.5	1.20±0.6	0.001*
LDL-c	(mmol/L)	2.41±0.8	2.82±0.7	3.52±1.04	3.04±0.1	0.017*
HDL-c	(mmol/L)	1.5±0.3	1.33±0.3	1.33±0.3	1.39±0.3	0.200
Albuminuria	(mg)	9.07±2.1	7.66±4.3	6.21±4.7	7.3±7.3	0.001*
Creatinuria	(mg)	115±75	143±79	173±76	149±79	0.200
GFR	mL/min/1.73m²	112±13	116±14	100±11	111±16	0.200
ALT	(IU/L)	13±9	14±7	25±17	19±14	0.001*
CCTR	(μm)	550±33	528±29	529±36	535±35	0.082
CCTL	(μm)	550±32	528±29	520±67	530±53	0.001*
CCETR	(μm)	59.8±4.5	57.1±4.6	63.1±5.9	60.8±5.7	0.029*
CCETL	(μm)	60.5±4.4	57.3±5.1	63±5.9	61±5.7	0.028*
BMI: Body mass index; WHR: Waist/hip ratio; NC: Neck circumference; BFP: Body fat percentage; SBP: Systolic blood pressures;
DBP: Diastolic blood pressures; HbA1c: Glycated haemoglobin; FPG: Fasting plasma glucose; 2h PPG: 2-hour post-load glucose;
FI: Fasting insulin; IR: Insulin resistant; FC-p: Fasting C-peptide; T col: Total cholesterol; TG: Triglyceride; ALT: Alanine aminotransferase;
LDL-c: Low-density lipoprotein cholesterol; HDL-c: High-density lipoprotein cholesterol; GFR: Glomerular filtration rate;
CCTR: Central corneal thickness right; CCTL: Central corneal thickness left; CCETR: Central corneal epithelial thickness right;
CCETL: Central corneal epithelial thickness left; n: Number; Mean±SD: Expressed as mean±standard deviation; F: female; M: male;
(*): Non-normally distributed variables; p values were calculated with the One-Sample Kolmogorov Smirnov test.

Table 2. Relationship of non-normally distributed variables according to groups
Group		Healthy control	Insulin resistant	Prediabetes	Pᵃ value	Pᵝ value	Pᵞ value
		Mean rank	Mean rank	Mean rank
Age	(year)	20.03	23.12	51.26	0.691*	0.001	0.001
NC	(cm)	15.84	27.81	48.18	0.037	0.001	0.001
SBP	(mmHg)	18.35	38.59	44.30	0.001	0.001	0.133*
DBP	(mmHg)	28.65	37	38.88	0.057*	0.017	0.459*
2h PPG	(mmol/L)	26	19	19.97	0.770*	0.084*	0.846*
IR		17.28	48.35	39.92	0.001	0.001	0.201*
TG	(mmol/L)	19.65	34.53	43.77	0.052*	0.001	0.186*
LDL-c	(mmol/L)	21.83	31.13	44.86	0.166*	0.001	0.018
Albuminuria	(mg)	35.29	36.94	28.68	0.122*	0.001	0.167*
ALT	(IU/L)	23.68	28.34	45.67	0.044*	0.001	0.003
CCTL	(μm)	44.43	31.41	31.03	0.030	0.045	0.823*
CCETR	(μm)	31.20	21.81	43.70	0.071*	0.001	0.001
CCETL	(μm)	32.98	21.44	42.80	0.024	0.002	0.001

NC: Neck circumference; SBP: Systolic blood pressures; DBP: Diastolic blood pressures; 2h PPG: 2-hour post-load glucose;

IR: Insulin resistant; TG: Triglyceride; LDL-c: Low-density lipoprotein cholesterol; ALT: Alanine aminotransferase;

CCTL: Central corneal thickness left; CCETR: Central corneal epithelial thickness right; CCETL: Central corneal epithelial thickness left;

Pᵃ: Group 1vs Group 2; Pᵝ: Group 1vs Group 3; Pᵞ: Group 2 vs Group 3;(*): Variables that did not differ between them;

p values were calculated with the Kruskal-Wallis test.

Table 3. The relationship of the normally distributed variables according to the groups
Group		Healthy control	Insulin resistant	Prediabetes
		Mini-Maxi	Mini-Maxi	Mini-Maxi	P value
BMI	(kg/m²)	16.1-25.9	18.2-33.2	19.6-36.6	0.001
WHR	(cm)	0.65-1.17	0.65-0.98	0.71-1.02	0.001
BFP	(%)	10.1-30.8	18.7-42	15.2-39.1	0.034
HbA1c	(%)	4.80-5.60	4.57-5.60	4.84-6.3	0.001
FPG	(mmol/L)	80-100	85-109	83.96-125.74	0.001
FI	(μU/mL)	3.27-22.11	11.37-24.39	2.68-31.8	0.001
FC-p	(ng/mL)	1.12-3.32	1.93-4.18	1-4.6	0.001
T col	(mmol/L)	104-204	143-252	154-361	0.001
HDL-c	(mmol/L)	31-79	28-77	33-93	0.130*
Creatinuria	(mg)	8.1-309	29.7-260	38.2-379	0.001
GFR	mL/min/1.73m²	90-138	90-136	76-120	0.001
CCTR	(μm)	508-635	491-595	475-616	0.074*

BMI: Body mass index; WHR: Waist/hip ratio; BFP: Body fat percentage; HbA1c: Glycated haemoglobin; FPG: Fasting plasma glucose;
FI: Fasting insulin; FC-p: Fasting C-peptide; T col: Total cholesterol; HDL-c: High-density lipoprotein cholesterol;
GFR: Glomerular filtration rate; CCTR: Central corneal thickness right; Mini-Maxi: Expressed as Minimum-Maximum;
(*): Variables that did not differ between them; p values were calculated with the One-Way ANOVA test.

Table 4. Correlation analysis of corneal parameters and demographic, anthropoemetric and biochemical data
		CCTR(μm)	CCTL(μm)	CCETR(μm)	CCETL(μm)
		r p	r p	r p	r p
Age	(year)	-.056 .649	-.052 .670	.367* .002	.293* .014
BMI	(kg/m²)	-.224 .067	-.245* .044	.210 .085	.141 .250
WHR	(cm)	.018 .882	.006 .962	.253* .037	.223 .068
NC	(cm)	-.086 .486	-.106 .391	.252* .038	.277* .022
BFP	(%)	-.306* .011	-.342* .004	.010 .934	-.013 .917
SBP	(mmHg)	-.234 .053	-.250* .038	.088 .474	.013 .918
DBP	(mmHg)	-.172 .157	-.177 .146	.232 .055	.228 .059
HbA1c	(%)	-.220 .069	-.221 .069	.441* .001	.334* .005
FPG	(mmol/L)	-.253* .036	-.269* .025	.371* .002	.271* .024
2h PPG	(mmol/L)	-.189 .248	-.209 .202	-.175 .285	-.048 .772
FI	(μU/mL)	-.150 .219	-.184 .130	-.138 .259	-.161 .187
IR		-.161 .186	-.200 .099	-.059 .629	-.100 .412
FC-p	(ng/mL)	-.170 .165	-.198 .105	.010 .914	.029 .811
T col	(mmol/L)	-.052 .677	-.077 .536	.254* .038	.201 .102
TG	(mmol/L)	-.087 .484	-.092 .461	.288* .018	.317* .009
LDL-c	(mmol/L)	-.056 .648	-.082 .508	.241* .048	.172 .160
HDL-c	(mmol/L)	-.121 .330	-.119 .337	-.221 .073	-.259* .035
Albuminuria	(mg)	-.140 .275	-.163 .201	-.070 .585	-.125 .330
Creatinuria	(mg)	.065 .605	.067 .595	.209 .095	.184 .142
GFR	mL/min/1.73m²	.076 .550	.079 .537	-.267* .033	-.270* .031
ALT	(IU/L)	.021 .865	-.004 .973	.153 .214	.118 .337

BMI: Body mass index; WHR: Waist/hip ratio; NC: Neck circumference; BFP: Body fat percentage; SBP: Systolic blood pressures;
DBP: Diastolic blood pressures; HbA1c: Glycated haemoglobin; FPG: Fasting plasma glucose; 2h PPG: 2-hour post-load glucose;
FI: Fasting insulin; IR: Insulin resistant; FC-p: Fasting C-peptide; T col: Total cholesterol; TG: Triglyceride; ALT: Alanine aminotransferase;
LDL-c: Low-density lipoprotein cholesterol; HDL-c: High-density lipoprotein cholesterol; GFR: Glomerular filtration rate;
CCTR: Central corneal thickness right; CCTL: Central corneal thickness left; CCETR: Central corneal epithelial thickness right;
CCETL: Central corneal epithelial thickness left; n: Number; Mean±SD: Expressed as mean±standard deviation; F: female; M: male;
(*): Non-normally distributed variables; p values were calculated with the One-Sample Kolmogorov Smirnov test.

No competing interests reported.

Highlights.docx

Relationship of Central Corneal Thickness and Central Corneal Epithelial Thickness with Anthropoemetric and Biochemical Data in Individuals with Impaired Glucose Metabolism

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Abstract

Background

Materials and Methods

Results

Discussion

Abbreviations

Declarations

References

Tables

Additional Declarations

Supplementary Files

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