Comparison of the macular vascular densities between molecularly confirmed MODY patients with GCK variants and age-matched healthy controls

doi:10.21203/rs.3.rs-2495369/v1

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Comparison of the macular vascular densities between molecularly confirmed MODY patients with GCK variants and age-matched healthy controls

https://doi.org/10.21203/rs.3.rs-2495369/v1

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Background: Several structural, vascular density and perfusion studies were conducted in type 1 and 2 diabetes, even in the absence of retinopathy. The current study is the first to compare macular vessel densities (VD) by optical coherence tomography angiography (OCTA) between maturity onset diabetes of the young (MODY) patients and healthy controls.

Methods: The macular VD of superficial, deep retina, and choriocapillaris, and central macular thickness (CMT), foveal avascular zone area (FAZ), FAZ perimetry, VD of total retina at 300µm around the FAZ (FD), acirculatory index (AI) measurements were captured by the OCTA, which operates with built into software (RTVue-XR100-2 Avanti, Angiovue), and were compared between molecularly confirmed (GCK mutations) MODY patients and controls.

Results: Twenty-five MODY patients and 30 controls were included. Mean plasma HbA1c level of the MODY group was 6.39±0.38 (min:5,4 max:6,9, %). Average age was 13.8±2.1 in the MODY group, and was 12.6±2.5 years among controls. There was no significant difference in terms of age, superficial and deep retinal VD, FAZ, FAZ perimetry, CMT, FD, and AI between groups. Significant increase of VD only at the parafoveal and perifoveal regions of choriocapillaris in the MODY group was observed (P=0.034 and P=0.009).

Conclusion: No significant difference of macular VD was observed between non-retinopathic MODY patients and controls, except VD of choriocapillaris at the parafovea and perifovea. Previous thickness and VD results were distributed in a wider range suggesting not yet defined factors may be affecting the choroidal vasculature independent of glycemia or as a contributing factor.

Health sciences/Risk factors

Health sciences/Medical research/Outcomes research

angiography

density

diabetes

MODY

vessel

vascular

Maturity onset diabetes of the young (MODY) is the prevalent form of monogenic diabetes with an autosomal dominant inheritance which currently consists of a heterogeneous group with 14 distinct subtypes [1–3]. The estimated prevalence of the disease from European cohorts is 1–5 per 10,000 that accounting for 1–5% of all of the diabetes cases, and the minimum estimated incidence is 2 per 1,000,000 below the age of 18 years per year [4–6]. The refined clinical features of MODY include; young-onset hyperglycemia (before 30 years of age), a history of diabetes in a first-degree relative, proof of residual pancreatic function, and lack of insulin resistance or beta cell autoimmunity [7]. The prevailing disorder among MODY patients is pancreatic β-cell dysfunction. These patients are usually misdiagnosed as type 1 or 2 diabetes due to the overlapping clinical signs and findings. Several clinical biomarkers are available, nevertheless none of them can be used as a single discriminator of the disease. For instance; autoantibody testing and C-peptide levels can be used to distinguish type 1 diabetes from MODY, and early-age of onset and lean body mass are applicable in discriminating MODY from type 2 diabetes [8, 9]. However, there is not any standardised algorithm or concise [7]. The diagnosis is commonly confirmed with molecular analyses while the clinical management and treatment of MODY can be subtype specific. By the development and widespread use of the targeted Next Generation Sequencing (NGS) technologies in clinical applications, diagnostic procedures of the genetically heterogeneous diseases have become efficient.

Optical coherence tomography angiography (OCTA) is an imaging modality with non-invasive and depth-resolved imaging ability of the retinal vasculature and structure [10]. A software supported map of vessel structure and depth resolved vascular flow is generated from the motion and blood flow of the same retinal position with multiple structural optic coherence tomography scans. The software of the OCTA also allows to calculate a ratio regarding vascular (or vessel) density (VD) of the retinal tissue [11, 12].

Several recent OCTA studies have been conducted to investigate the vascular density (VD) comparison by optical coherence tomography angiography (OCTA) in retinal vascular threatening diseases, also in diabetes. The OCTA based VD and relevant parameters were mostly studied in type 1 and type 2 diabetic patients represented with and without diabetic retinopathy (DRP). However, to the best of our knowledge; there is no published article regarding OCTA parameters of the MODY in the PubMed database by 21st September 2022. The aim of the current study is; to investigate and compare the macular VD of OCTA scans between in molecularly confirmed MODY patients and their age-matched healthy controls.

Ethics

The study was carried out with a prospective observational cross-sectional case-control design, and involved human participants, and conducted between June 2020 and December 2021. All of the procedures and clinical interventions performed in the study were in accordance with the ethical standards of the local institutional ethics committee (1st Ethics Committee of Ankara City Hospital, Date:02.04.2020, Approval number: El/409/2020), and the Declaration of Helsinki (1964) and its later amendments. Both of the informed consents of patients and their relatives (or legal guardians) were obtained. The procedures were also applicated for the healthy controls.

Clinical Evaluation and Exclusion Criteria

The diagnosis criteria of diabetes are based on plasma glucose level and were applied in the study as follows; a random plasma glucose ≥ 200 mg/dL, or fasting plasma glucose ≥ 126 mg/dL or glycosylated haemoglobin (HbA1c) ≥ 6.5% or 2-hour plasma glucose value during an oral glucose tolerance test (OGTT) ≥ 200mg/dl [13]. The diagnosis of MODY was suspected especially in individuals with positive family history of diabetes, without any typical feature of type 1 or type 2 diabetes (diabetes associated autoantibodies or obesity), and with mild and stable fasting hyperglycemia and/or HbA1C. The study comprised follow-up patients aged between 12–17 with a disease duration of 1 to 5 years, and molecularly confirmed diagnosis of MODY. Gender, body mass index (BMI), age of diagnosis, duration of the disease, fasting plasma glucose, glycosylated haemoglobin (HbA1c), routine blood and urine tests regarding liver, pancreas and kidney functions, previous and current medical treatment features of the patients were all asked and investigated by a pediatric endocrinologist. Subjects having; a mean BMI over 30, and a mean HbA1c over 7.0% (that exceeds the target or reasonable value for diabetes control according to the 2018 International Society of Pediatric and Adolescent Diabetes Guidelines) during their visits in the year [14], comorbidity, clinical or laboratory suspicious results regarding vasculopathy, nephropathy, and neuropathy of diabetes, body developmental measures below the 10th and over the 90th percentiles, a history and/or a suspicious finding associated with any systemic disease other than MODY, premature birth, and smoking were excluded.

Molecular Analyses

The molecular analyses had been carried out using the DNA extracted from the peripheral lymphocytes. A targeted NGS panel including the GCK gene (Qiagen, Hilden Germany) was studied on the Myseq™ system (Illumina) and analysed with the Qiagen Clinical Insight platform. Variants were prioritized and classified according to the recommendations of the American College of Medical Genetics and Genomics guidelines in terms of frequency, in-silico analysis, clinical correlation, evolutionary conservation, effect on amino acid, and replacement on the protein [15]. All included patients in this study had either a pathogenic or likely pathogenic variant of the GCK gene (Fig. 1). For detailed information, see the supplementary data/supporting information (Supplemental Table 1).

Ophthalmological Evaluation and Exclusion Criteria

All patients underwent detailed ophthalmological examination, including assessment of Snellen best-corrected visual acuity (BCVA), a slit-lamp biomicroscopy and indirect funduscopy, colour fundus photographs, and intraocular pressure (Tonopachy NT-530P, Nidek Co, Tokyo). OCTA images were obtained by RTVue-XR100-2 Avanti (Angiovue, Optovue, Inc, Freemont, CA, USA), which operates via a light wavelength of 840 nm and a bandwidth of 45 nm, and a speed of 70 000 A-scans per second. The motion correlation technology and split spectrum amplitude decorrelation angiography algorithm (SSADA) built into the Angiovue system. The Angio Analytic software which is a built-in support to the current OCTA device can also calculate the macular vascular density automatically.

The OCTA scanning was performed by a technician who was blinded to the subject details. All OCTA measurements were performed between 9:00 and 11:00 hours to prevent possible diurnal variations [16]. A 6 × 6 mm frame centred on the fovea was scanned on the macular HD module. After image acquisition, en-face screenings were segmented to define the layers (superficial, deep, outer retinal) using the ‘built-in automatic segmentation’ algorithm of the device. Screenings with a signal strength index below 40 and a central macular thickness over 300µm (due to any type of macular oedema and/or diffuse thickening of intraretinal layers and/or any type of intra retinal fluid), and unreliable scans (due to disruption of the microvascular structure) were excluded to standardise the results between groups [17]. The automated angio-analytic software of version 2018.1.0.43 was used for the analysis of superficial macular (VD-SP, the segmentation was adjusted between 3 µm below the internal limiting membrane and 15 µm below the inner line of internal plexiform layer), deep macular (VD-DP, from 15 µm below the inner line of the internal plexiform layer to 70 µm below the inner border of the inner plexiform retinal layer) and choriocapillaris (VD-CC, 30 µm below the junction of the retinal pigment epithelium and Bruch’s membrane) structures (%) [18–20]. Also, foveal avascular zone (FAZ) area (mm²), FAZ perimetry (mm), total retinal VD 300µm around the FAZ perimetry (FD, %), acirculatory index (AI) which shows the ratio between perimeter of the FAZ to perimeter of a circle with equal area [21, 22]. In addition, central macular thickness (CMT) values were captured from the software of the device (µm) (Supplemental Fig. 1).

Subjects currently having any relevant examination finding or history of the followings; corneal opacities or corneal ectatic diseases, morphologic and locational lens abnormalities and cataracts, uveitis and relevant other inflammatory conditions, vitreous diseases, inflammation and opacities affecting the quality of the scanning, retinal, macular, optic disc and choroidal funduscopic abnormalities and their vascular involvements, autoimmune or microbial originated vasculitis, sequels of ocular trauma or surgery, chronic systemic or local diseases or any type of systemic/local/topical medication uptake in the last one month, refractive deficiencies greater than ± 3.0 diopters of spherical equivalence or axial length ≥ 26 mm, eyes having intraocular pressure greater than 21 mm HG, and scanning reports of signal strength index under 50 of the OCTA assessments were excluded.

All patients and controls were coded with a consecutive number according to the time of their inclusion. Eyes of the subjects were included accordingly for randomization; only the right eyes of the subjects with an odd number, and their left eyes who were coded with an even number.

Statistical Analyses

Statistical analyses were performed by using the SPSS version 17.0 (Chicago, IL, USA). The quantitative measurements were given as the means and standard deviations (SD), and their minimum and maximum values. The normality of the data was assessed by the Shapiro-Wilk test. Levene's test was used to test the equality of variances of the groups in terms of age (years) and spherical equivalency (in diopters). Also, the significancy of difference of distribution of gender between groups were tested by the chi-square test. The Mann-Whitney U test was used to compare differences between the independent measurements when the variable is either continuous or ordinal, but not distributed normally. A P-value < 0.05 is considered as statistically significant.

Molecularly verified 25 (9 male, 16 female) patients of MODY type 2 and 30 healthy controls (14 male, 16 female) were included into the study. The mean age was 13.8±2.1 in the MODY group, and was 12.6±2.5 for the controls. There was no significant difference in terms of age and distribution of gender between groups (p=0.093 and p=0.6, respectively). The mean spherical equivalences of refractive errors in diopters were -0.36 ±1.2, and -0.16±1.4 in the MODY, and in the control group, respectively. There was not any significant difference between groups (p=0.56). The mean plasma HbA1c level of the MODY group was 6.39±0.38 (min:5,4 max:6,9, %).

The comparison of the VD of the superficial and deep macular OCTA segmentations is shown on Table 1 and Table 2 respectively. No significant difference in terms of evaluated parameters was observed between groups. As well, the vessel densities of the choriocapillaris were investigated. Significant increase of VD in the MODY group was detected at the parafoveal, and perifoveal region in the choriocapillaris segmentations, and those details are shown on Table 3. The degree of significance in terms of VD-CC at the macula increased throughout the distance from the fovea (in parafovea and perifovea respectively). In addition, the measurements of FAZ area, FAZ perimetry, AI, and FD were compared between groups, and no significant change was observed (Table 4).

Thirteen different GCK variants, one of which was novel, have been determined in 25 patients from 23 families. The most common variants were c.1178T>C (p.Met393Thr) detected in 8 unrelated patients, c.208+3A>T in 4 patients. There were 2 siblings from two different families in this study sharing the c.781G>C (p.Gly261Arg) and c.1079C>G (p.Ser360Trp) variants respectively. Of the 13 variants, 1 was nonsense, 2 were splice-site, and others were all missense variants. Three variants were located on the small hexokinase domain while 5 of them were on the large hexokinase domain.

Several recent studies investigated and reported the vascular density changes of the retinal vasculature and choriocapillaris in diabetic children and adults with DRP or without DRP, and compared them with healthy controls. However, currently there is no available report assessing the microvascular changes in the specific subtype of diabetes of MODY, and any comparison with controls. The current study included not only the clinical diagnosed MODYs, but also molecularly confirmed patients. It is noteworthy to investigate possible specific vascular changes in this specific subgroup of the diabetes or to assess whether the structural components are similar or not to the other types diabetes for controlling and managing the disease effectively.

The structural and flow calculation abilities of the retinal vasculature in the OCTA software might directed researchers to apply OCTA in the diagnose of preclinical DRP, and along with primary care partners to achieve a better clinical and ophthalmological outcome by controlling glycemia, blood pressure and other biochemical components. Across these studies, there is no widely accepted consensus on the vascular densities or perfusion changes of retinal plexus and choriocapillaris according to the recent OCTA studies comparing the non-DRP patients and healthy controls [20, 23–26]. However, patients with non-proliferative DRP or proliferative DRP mostly represented with decreased vessel and perfusion densities and increased FAZ dimensions [23, 25, 27]. In addition to all, Battista et al. concluded that OCTA has come along as an indispensable device for understanding the vascular background in the role of diabetic retinopathy which is not free of limitations such as segmentation errors and/or motion artifacts [28].

A recent meta-analysis scoping 45 of the OCTA studies conducted in the relevant objective, compared diabetic patients with no clinical DRP findings and healthy controls. OCTA results of diabetic patients revealed; decreased VD in superficial and deep capillary plexuses of the macula, increased perimeter of the foveal avascular zone, and reduced VD in radial peripapillary capillaries. Additionally, most of those differences were resulted as nonsignificant (except parafoveal VD of deep capillaries) in type 1 diabetes, while they remained significant in type 2 diabetes according to the subgroup analyses [29].

It is proposed that disruption of vascular arcades around the FAZ area even in the early stages of DRP can be detected by OCTA assessments, and may be differentiated from healthy controls [30]. Significant differences were also resulted in terms of FAZ area and perimetry in patients without DRP [22]. The macular FAZ area, FAZ perimetry, FD and AI values of MODY subjects did not differ significantly from controls in the current study. In addition, the superficial and deep retinal VDs in the MODY group did not change significantly in the study. Those insignificant outcomes may be related to the relatively acceptable or good glycemia control (HbA1c < 7%) of the designated group, young age status, relatively good prognostic nature of the MODY type (GCK, type 2) [31], absence of any systemic comorbidity, and low diabetes duration of the included patients. However, slight but significant increase in the mean CC VD at the parafoveal and perifoveal region was observed in the MODY group (70.8 ± 3.3 vs 69 ± 3.5, and 73.5 ± 2.2 vs 71.3 ± 3.2, respectively). Interestingly, the degree of significance increased with distance from the fovea centre along the periphery of the retina (P = 0.034 vs P = 0.009). Agra CLDM et al. compared the OCTA results between type 2 diabetes and controls with a close objective and methodology to our study, and they reported no difference on the superficial and deep VDs and FAZ area, and resulted slight but significant excess of CC flow area (mm²) resembling our results. They discussed OCTA may not be in the expected position for ensuring an early diagnosis of DRP, and nowadays it cannot replace the clinical funduscopic examinations due to their statistically significant, but clinically insignificant changes [20].

CC, which is a dense vascular network is essential for nutrition and oxygen supply of the outer retinal cells such as photoreceptors and retinal pigment epithelium to maintain normal vision [32]. Previous studies investigated the status of choroid in diabetes and DRP, and there is no widely accepted consensus regarding thickness of choroid. Some of them reported decrease in choroidal thickness even in the absence of DRP in diabetics [33–36], and some of them reported thickening along DRP progression, and also in patients without DRP [37–39]. Of the authors Ferreira et al. concluded that there is a prone to choroidal thickening in those without DRP. In addition, an OCTA study conducted by Ferrara et al. in various stages of diabetes including no DRP, non-proliferative DRP, and proliferative DRP cases concluded that vascular remodelling observed in all types of diabetes was associated to tortuous, beaded irregular choroidal vessels with focal narrowing and dilation [40]. Furthermore, Jo Y. et al found a correlation between increased choroidal thickness and HbA1c levels in diabetics who were hospitalised for control of glycemia [41]. These outcomes suggest that this tissue may be functioning differently in diabetes, and the pattern of influence appears to vary between different phases.

Researchers of the DRCR.net compared the CMT values in diabetic patients who had either minimal or no DRP with healthy controls. They concluded that diabetes without DRP findings is not associated with significant CMT changes which was consistent with the outcomes of the current study in terms of macular thickness [42].

Previous studies suggested that degeneration in neuro-retinal cells can be one of the primary detectable retina abnormalities in diabetes, and can precede microvascular complications. However, until today, the exact mechanism of relationship between retinal neuronopathy and vascular alterations has not been described exhaustively [43, 44].

In conclusion, no significant difference in terms of macular VD assessment between non-retinopathic MODY patients and controls was observed, except VD of CC at the parafovea and perifovea. According to previous various structural and VD of choriocapillaris, there may be sundry demographic, genetic and/or other undetermined factors affecting the choroidal vasculature independent of glycemia or as a contributing factor. Current findings need to be confirmed by prospective and consecutive measurements in larger case series having longer follow-up. Also, the background reasons for the current results can be better understood by further studies conducted in the scope to reveal the probable effects of diabetes in neuro-retinopathy, choroidopathy and/or ocular neuro-vascular innervations. Development in ocular imaging modalities may further characterise the choroidopathy of diabetes in the near future.

Author Contribution Information

All authors contributed to the study conception and design. Material preparation and data collection and analysis were performed by Cemal Çavdarlı, Gönül Büyükyılmaz, Büşranur Çavdarlı and Sebile Çomçalı. Pınar Topcu Yılmaz and Mehmet Numan Alp analysed the outcomes and made important intellectual contribution. The first draft of the manuscript was written by Cemal Çavdarlı, Gönül Büyükyılmaz, and Büşranur Çavdarlı and all authors commented on previous versions of the manuscript. All authors read and approved the final version of the manuscript.

Disclosure Statement

The authors report no conflicts of interest.

Funding

No funding or sponsorship was received for this study or publication of this article.

Flannick J, Johansson S, Njølstad PR. Common and rare forms of diabetes mellitus: towards a continuum of diabetes subtypes. Nat Rev Endocrinol. 12(7):394-406 (2016). doi:10.1038/NRENDO.2016.5
Sanyoura M, Philipson LH, Naylor R. Monogenic Diabetes in Children and Adolescents: Recognition and Treatment Options. Curr Diabetes Reports 2018 188.18(8):1-13 (2018). doi:10.1007/S11892-018-1024-2
Nkonge KM, Nkonge DK, Nkonge TN. The epidemiology, molecular pathogenesis, diagnosis, and treatment of maturity-onset diabetes of the young (MODY). Clin Diabetes Endocrinol. 6(1):20 (2020). doi:10.1186/S40842-020-00112-5
Owen K. Orphanet: MODY. Noviembre. Published 2014. Accessed on March 13, 2022. https://www.orpha.net/consor/cgi-bin/OC_Exp.php?Lng=GB&Expert=552
Firdous P, Nissar K, Ali S, Ganai BA, Shabir U, Hassan T, et al. Genetic Testing of Maturity-Onset Diabetes of the Young Current Status and Future Perspectives. Front Endocrinol (Lausanne). 9:253 (2018). doi: 10.3389/fendo.2018.00253.
Amed S, Dean HJ, Panagiotopoulos C, Sellers EA, Hadjiyannakis S, Laubscher TA, et al. Type 2 diabetes, medication-induced diabetes, and monogenic diabetes in Canadian children: a prospective national surveillance study. Diabetes Care. 33(4):786-91 (2010). doi: 10.2337/dc09-1013.
Urbanová J, Brunerová L, Brož J. Hidden MODY-Looking for a needle in a Haystack. Front Endocrinol (Lausanne). 9:355 (2018) doi:10.3389/FENDO.2018.00355/BIBTEX
Amed S, Oram R. Maturity-Onset Diabetes of the Young (MODY): Making the Right Diagnosis to Optimize Treatment. Can J Diabetes. 40(5):449-454 (2016). doi:10.1016/j.jcjd.2016.03.002
Rafique I, Mir A, Saqib MAN, Naeem M, Marchand L, Polychronakos C. Causal variants in Maturity Onset Diabetes of the Young (MODY) – A systematic review. BMC Endocr Disord. 21(1):1-6 (2021). doi:10.1186/S12902-021-00891-7/FIGURES/4
Jia Y, Tan O, Tokayer J, Potsaid B, Wang Y, Liu JJ, et al. Split-spectrum amplitude-decorrelation angiography with optical coherence tomography. Opt Express. 20(4):4710-25 (2012). doi: 10.1364/OE.20.004710.
Gao SS, Jia Y, Zhang M, Su JP, Liu G, Hwang TS, et al. Optical Coherence Tomography Angiography. Invest Ophthalmol Vis Sci. 57(9): OCT27-36 (2016). doi: 10.1167/iovs.15-19043.
Chua J, Sim R, Tan B, Wong D, Yao X, Liu X, et al. Optical Coherence Tomography Angiography in Diabetes and Diabetic Retinopathy. J Clin Med. 9(6):1723 (2020). doi: 10.3390/jcm9061723.
Mayer-Davis EJ, Kahkoska AR, Jefferies C, Dabelea D, Balde N, Gong CX, et al. ISPAD Clinical Practice Consensus Guidelines 2018: Definition, epidemiology, and classification of diabetes in children and adolescents. Pediatr Diabetes. 19 Suppl 27(Suppl 27):7-19 (2018). doi: 10.1111/pedi.12773
[website, accessed on 23th November 2022] DiMeglio LA, Acerini CL, Codner E, Craig ME, Hofer SE, Pillay K, Maahs DM. Chapter 8: Glycemic control targets and glucose monitoring for children, adolescents with Diabetes. International Society of Pediatric and Adolescent Diabetes (ISPAD). url: https://www.ispad.org/page/Guidelines2018Chap8
Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, et al. ACMG Laboratory Quality Assurance Committee. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med.17(5):405-24 (2015). doi: 10.1038/gim.2015.30.
Kinoshita T, Mitamura Y, Shinomiya K, Egawa M, Iwata A, Fujihara A, et al. Diurnal variations in luminal and stromal areas of choroid in normal eyes. Br J Ophthalmol. 101(3):360-364 (2017). doi: 10.1136/bjophthalmol-2016-308594.
Çavdarli C, Çavdarli B, Topcu-Yilmaz P, Polat Gültekin B. Optical coherence tomography-angiographic vascular densities in Familial Mediterranean Fever (FMF) Patients with M694V Mutations. Ophthalmic Genet. 41(3):257-262 (2020). doi:10.1080/13816810.2020.1759108
Coscas F, Sellam A, Glacet-Bernard A, Jung C, Goudot M, Miere A, et al. Normative Data for Vascular Density in Superficial and Deep Capillary Plexuses of Healthy Adults Assessed by Optical Coherence Tomography Angiography. Invest Ophthalmol Vis Sci. 57(9): OCT211-23 (2016). doi: 10.1167/iovs.15-18793.
Agemy SA, Scripsema NK, Shah CM, Gentile RC, Hsiao Y, Zhou Q. Retinal vascular perfusion density mapping using optical coherence tomography angiography in normals and diabetic retinopathy patients. Retina 35(11):2353-63 (2015)
Agra CLDM, Lira RPC, Pinheiro FG, Sá LHSE, Bravo Filho VTF. Optical coherence tomography angiography: microvascular alterations in diabetic eyes without diabetic retinopathy. Arq Bras Oftalmol. 84(2):149-157 (2021). doi: 10.5935/0004-2749.20210023.
Yasin Alibhai A, Moult EM, Shahzad R, Rebhun CB, Moreira-Neto C, McGowan M, et al. Quantifying Microvascular Changes Using OCT Angiography in Diabetic Eyes without Clinical Evidence of Retinopathy. Ophthalmol Retina. 2(5):418-427 (2018). doi: 10.1016/j.oret.2017.09.011.
Krawitz BD, Mo S, Geyman LS, Agemy SA, Scripsema NK, Garcia PM, et al. Acircularity index and axis ratio of the foveal avascular zone in diabetic eyes and healthy controls measured by optical coherence tomography angiography. Vision Res. 139:177-186 (2017). doi: 10.1016/j.visres.2016.09.019
Conti FF, Qin VL, Rodrigues EB, Sharma S, Rachitskaya AV, Ehlers JP, et al. Choriocapillaris and retinal vascular plexus density of diabetic eyes using split-spectrum amplitude decorrelation spectral-domain optical coherence tomography angiography. Br J Ophthalmol. 103(4):452-456 (2019). doi: 10.1136/bjophthalmol-2018-311903.
Stulova AN, Semenova NS, Zheleznyakova AV, Akopyan VS, Lipatov DV. OCTA and Functional Signs of Preclinical Retinopathy in Type 1 Diabetes Mellitus. Ophthalmic Surg Lasers Imaging Retina. 52(S1): S30-S34 (2021) doi: 10.3928/23258160-20210518-06.
Choi W, Waheed NK, Moult EM, Adhi M, Lee B, De Carlo T, et al. Ultrahigh speed swept source optical coherence tomography angiography of retinal and choriocapillaris alterations ın diabetıc patients with and without retinopathy. Retina. 37(1):11-21 (2017). doi: 10.1097/IAE.0000000000001250.
Vujosevic S, Muraca A, Alkabes M, et al. Early Mıcrovascular And Neural Changes In Patıents Wıth Type 1 And Type 2 Dıabetes Mellıtus Wıthout Clınıcal Sıgns Of Dıabetıc Retınopathy. Retina. 39(3):435-445 (2019). doi: 10.1097/IAE.0000000000001990.
Agemy SA, Scripsema NK, Shah CM, Chui T, Garcia PM, Lee JG, et al. Retinal vascular perfusion density mapping using optical coherence tomography angiography in normals and diabetic retinopathy patients. Retina. 35(11):2353-63 (2015). doi: 10.1097/IAE.0000000000000862.
Battista M, Borrelli E, Sacconi R, Bandello F, Querques G. Optical coherence tomography angiography in diabetes: A review. Eur J Ophthalmol. 30(3):411-416 (2020). doi: 10.1177/1120672119899901.
Zhang B, Chou Y, Zhao X, Yang J, Chen Y. Early Detection of Microvascular Impairments With Optical Coherence Tomography Angiography in Diabetic Patients Without Clinical Retinopathy: A Meta-analysis. Am J Ophthalmol. 222:226-237 (2021). doi:10.1016/J.AJO.2020.09.032
Freiberg FJ, Pfau M, Wons J, Wirth MA, Becker MD, Michels S. Optical coherence tomography angiography of the foveal avascular zone in diabetic retinopathy. Graefes Arch Clin Exp Ophthalmol. 254:1051–1058 (2016).
Delvecchio M, Pastore C, Giordano P. Treatment Options for MODY Patients: A Systematic Review of Literature. Diabetes Ther. 11(8):1667-1685 (2020) doi: 10.1007/s13300-020-00864-4.
Mulfaul K, Russell JF, Voigt AP, Stone EM, Tucker BA, Mullins RF. The Essential Role of the Choriocapillaris in Vision: Novel Insights from Imaging and Molecular Biology. Annu Rev Vis Sci. 8:33-52 (2022). doi: 10.1146/annurev-vision-100820-085958.
Querques G, Lattanzio R, Querques L, Del Turco C, Forte R, Pierro L, et al. Enhanced depth imaging optical coherence tomography in type 2 diabetes. Invest Ophthalmol Vis Sci. 53(10):6017-24 (2012). doi: 10.1167/iovs.12-9692.
Esmaeelpour M, Brunner S, Ansari-Shahrezaei S, Nemetz S, Povazay B, Kajic V, et al. Choroidal thinning in diabetes type 1 detected by 3-dimensional 1060 nm optical coherence tomography. Invest Ophthalmol Vis Sci. 53(11):6803-9 (2012). doi: 10.1167/iovs.12-10314.
. Esmaeelpour M, Považay B, Hermann B, Hofer B, Kajic V, Hale SL, et al. Mapping choroidal and retinal thickness variation in type 2 diabetes using three-dimensional 1060-nm optical coherence tomography. Invest Ophthalmol Vis Sci. 15;52(8):5311-6 (2011). doi: 10.1167/iovs.10-6875.
Vujosevic S, Martini F, Cavarzeran F, Pilotto E, Midena E. Macular and peripapillary choroidal thickness in diabetic patients. Retina. 32(9):1781–1790 (2012).
Lee HK, Lim JW, Shin MC. Comparison of choroidal thickness in patients with diabetes by spectral-domain optical coherence tomography. Korean J Ophthalmol. 27(6):433–439 (2013).
Kim JT, Lee DH, Joe SG, Kim JG, Yoon YH. Changes in choroidal thickness in relation to the severity of retinopathy and macular edema in type 2 diabetic patients. Investig Ophthalmol Vis Sci. 54(5):3378–3384 (2013).
Ferreira JT, Vicente A, Proença R, Santos BO, Cunha JP, Alves M, et al. Choroidal thickness in diabetic patients without diabetic retinopathy. Retina. 38(4):795-804 (2018). doi: 10.1097/IAE.0000000000001582.
Ferrara D, Waheed NK, Duker JS. Investigating the choriocapillaris and choroidal vasculature with new optical coherence tomography technologies. Prog Retin Eye Res. 52:130-55 (2016). doi: 10.1016/j.preteyeres.2015.10.002
Jo Y, Ikuno Y, Iwamoto R, Okita K, Nishida K. Choroidal thickness changes after diabetes type 2 and blood pressure control in a hospitalized situation. Retina. 34(6):1190-8 (2014).
Wiley HE, Ferris III FL. Nonproliferative diabetic retinopathy and diabetic macular edema. In: Ryan SJ, editor. Retina. (Londres: Elsevier Saunders, 2013) p. 940-68.
Reis A, Mateus C, Melo P, Figueira J, Cunha-Vaz J, CasteloBranco M. Neuroretinal dysfunction with intact bloodretinal barrier and absent vasculopathy in diabetes type 1. Diabetes 63:3926–3937 (2014).
Yoshida A, Kojima M, Ogasawara H, Ishiko S. Oscillatory potentials and permeability of the blood-retinal barrier in noninsulin-dependent diabetic patients without retinopathy. Ophthalmology 98:1266–1271 (1991)

Table 1. Superficial macular vessel density means, minimum and maximum values of the groups, and assessment of the statistical significancy (Statistical significance for The Mann-Whitney U-test, p<0.05).

*Parameter*	*Group*	*Mean*	*Min*	*Max*	*Median*	P
CMT	MODY	242±13	222	263	244	0.774
CMT	Control	243±20	203	280	243	0.774
VD superficial whole	MODY	47.2±3.5	38.4	52.6	47.8	0.735
VD superficial whole	Control	47.8±3.3	41.1	54.4	47.7	0.735
VD superficial fovea	MODY	20.1±6.1	8.6	32	19	0.89
VD superficial fovea	Control	20±6.3	5.2	33.6	19.7	0.89
VD superficial parafovea	MODY	48.4±5.3	33.5	53.8	50.3	0.993
VD superficial parafovea	Control	48.7±4.9	40.5	57.7	48.4	0.993
VD superficial perifovea	MODY	47.6±3.4	39	53	48	0.561
VD superficial perifovea	Control	48.3±3.4	40.8	54.9	49.3	0.561

CMT: central macular thickness, MODY: type 2 MODY patients, VD: vessel density

Table 2. Macular vessel density means in deep segmentations, and minimum and maximum values of the groups, and assessment of the statistical significancy of the variables. (Statistical significance for The Mann-Whitney U-test, p<0.05)

*Parameter*	*Group*	*Mean*	*Min*	*Max*	*Median*	P
VD deep whole	MODY	47.5±5	38.4	55.6	48.5	0.761
VD deep whole	Control	47.5±5.7	34.4	55	49.2	0.761
VD deep fovea	MODY	37.1±7	24.6	49.9	36.4	0.855
VD deep fovea	Control	37.4±7.2	23.2	50.2	36.9	0.855
VD deep parafovea	MODY	54.3±4	47.2	60.6	54.5	0.549
VD deep parafovea	Control	54.4±5.5	42	61.6	54.9	0.549
VD deep perifovea	MODY	48.4±5.3	39.3	56.9	49.8	0.855
VD deep perifovea	Control	48.1±6.3	34	56.6	50	0.855

MODY: type 2 MODY patients, VD: vessel density

Table 3. The vessel density means of choriocapillaris level, and minimum and maximum values of the groups, and assessment of the statistical significancy between groups. (Statistical significance for The Mann-Whitney U-test, p<0.05)

*Parameter*	*Group*	*Mean*	*Min*	*Max*	*Median*	P
VD-CC whole	MODY	71.9±2.6	66.6	76.9	71.7	0.072
VD-CC whole	Control	70.5±3.1	63.3	75	71.1	0.072
VD-CC fovea	MODY	71.7±4.7	61.3	80.1	71.7	0.945
VD-CC fovea	Control	70.8±6.6	57.5	79.8	72.9	0.945
VD-CC parafovea	MODY	70.8±3.3	63.1	76.2	71.1	0.034
VD-CC parafovea	Control	69±3.5	61.5	75.6	69.7	0.034
VD-CC perifovea	MODY	73.5±2.2	70.3	77.8	74.1	0.009
VD-CC perifovea	Control	71.3±3.2	63.8	75.9	71.2	0.009

CC: choriocapillaris MODY: type 2 MODY patients, VD: vessel density

Table 4. Assessment of foveal avascular zone (FAZ) area (mm²), FAZ perimetry (mm), acirculatory index (AI), and total retinal vessel density (VD) 300µm around the FAZ perimetry (FD, %), and their statistical comparison between groups (Statistical significance for The Mann-Whitney U-test, p<0.05).

*Parameter*	*Group*	*Mean*	*Min*	*Max*	*Median*	P
FAZ area	MODY	0.26±0.1	0.09	0.44	0.26	0.965
FAZ area	Control	0.26±0.1	0.09	0.46	0.25	0.965
FAZ perimetry	MODY	1.9±0.4	1.2	2.8	2	0.978
FAZ perimetry	Control	1.9±0.4	1.2	2.6	2	0.978
AI	MODY	1.08±0.02	1.04	1.14	1.08	0.394
AI	Control	1.08±0.02	1.05	1.11	1.08	0.394
FD	MODY	52.4±5.3	35.7	59.4	53.4	0.561
FD	Control	51.9±6	35.7	59.3	52.9	0.561

MODY: type 2 MODY patients

There is no conflict of interest

Suppl.Tablemodyocta.docx
Supplemental Table 1. Patients with heterozygous disease-causing GCK gene variants are summarized in terms of age, gender, and variant features.
Fig2modyoctacomp300supplfig2.jpg
Supplemental Figure 1. Representative 6 × 6-mm enface OCTA vascular density assessment used for quantification of the superficial and deep retinal layers and the choriocapillaris and corresponding vascular density percentages (A, B and C, respectively), and representative image for the foveal avascular zone (FAZ) (non-flow) area (mm²), FAZ perimetry (mm), total retinal vessel density 300µm around the FAZ perimetry (FD, %), acirculatory index (AI) and central macular thickness assessment of the OCTA software (D, E and F, respectively)

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Comparison of the macular vascular densities between molecularly confirmed MODY patients with GCK variants and age-matched healthy controls

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Clinical Evaluation and Exclusion Criteria

Molecular Analyses

Ophthalmological Evaluation and Exclusion Criteria

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