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Introduction

Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary kidney disease, with a prevalence of 1:400 to 1:1000 in Caucasians. It is caused by mutations in the PKD1 gene located on chromosome 16p13.3 [1] (in approximately 85% cases) as well as in the PKD2 gene on chromosome 4q13-23 [2]. These genes encode the polycystin-1 (PC-1) and polycystin-2 (PC-2) proteins [3]. PC-1 and PC-2 assemble in the plasma membrane to regulate the calcium (Ca2+) entry mechanism. The other biological functions of polycystins (PCs) are still under investigation [4].

The presence of kidney cysts is a characteristic feature in ADPKD patients and is necessary to establish the diagnosis [5]. Cystic pathology in the course of ADPKD is believed to be the result of abnormal cell proliferation and deregulated apoptosis [6]. Cysts may cause abdominal pain, hematuria and infection [7]. The number and diameter of cysts increases with age [8], which leads to progressive renal enlargement and subsequent loss of kidney function [9]. By the age of 60 years, half of ADPKD patients develop chronic end-stage kidney disease (ESRD), requiring kidney replacement therapy [10]. In developed countries, patients with ADPKD constitute 4–10% of all patients undergoing dialysis. In ADPKD, cyst generation and enlargement are associated with transformed vascular architecture: microvasculature tends to develop the regression of larger capillaries with flattened arterioles. It can be the result of reduced expression of the polycystins in the vasculature, where they are important for mechanosensation, fluid-shear stress sensing, signaling, and preserving structural integrity [11, 12, 13]. Vascular endothelial growth factor (VEGF) is an angiogenic cytokine playing pivotal roles in the maintenance of vascular networks; the VEGF family is chronically downregulated in ADPKD. Moreover, many cells in ADPKD aberrantly express VEGF, which in turn stimulates interstitial fibroblasts and endothelial cells, contributing to disease progression [14]. Abnormal kidney function due to polycystic kidney disease may result in systemic osmotic imbalances resulting from hyponatremia, which causes an osmotic gradient across the vascular interface. Interestingly, VEGF acting via VEGF receptor-2 can induce a release of glutamate from Müller cells, a type of retinal glial cell, which serve as support cells for retinal neurons, preventing cellular swelling of Müller glia in hypoosmotic stress [15]. Under prolonged osmotic stress conditions, the local production of reactive oxygen species (ROS) is induced, which is associated with the development of different chronic inflammatory retinal diseases, such as exudative age-related macular degeneration, diabetic retinopathy, uveitis, or atherosclerotic vascular retinal disorders [16, 17, 18].

In ADPKD patients, cardiovascular abnormalities are significantly more common than in the general population, including hypertension (HT), higher left ventricular mass or cardiac valvular defects, and intracranial and extracranial aneurysms [19]. Intracranial aneurysms occur in 4–8% of patients with ADPKD and in 25–50% may cause intracranial bleeding [20]. In ADPKD patients, especially 40–50-year-olds, subarachnoid bleeding occurs 5 times more often than in the general population and causes 5% of deaths among those patients [21]. In the general population, analysis of retinal vessels according to the Keith-Wagener classification [22] can serve as a predictive marker for the occurrence, clinical course, and prognosis of cerebrovascular and cardiovascular diseases. Retinal vessel analysis (RVA) is a modern methodological approach that is used to analyze retinal vessel caliber and vascular function in the retinal microcirculation [23]. The association of retinal vessel caliber abnormalities, such as arteriolar narrowing (AN) and a lower arteriovenous ratio (AVR), with HT and chronic kidney disease has been shown [24, 25, 26]. The width of the arterial vessels at the level of the retina depends on the age and gender, and as a person ages, the arterial vessels gradually narrow [27]. To date, no studies on the advancement of vascular changes have been performed in the retinal microcirculation of ADPKD patients.

The aim of this study was to analyze in detail the retinal vessel quality in ADPKD patients with normal kidney function and without concurrent diabetes mellitus (DM), using standard ophthalmological examination and RVA testing, and to compare it to a non-ADPKD control group. We also wanted to verify the hypothesis that retinal vessels in ADPKD patients may contain microaneurysms, as is are typical in the other vascular beds of ADPKD subjects, and to determine whether ADPKD may be a risk factor for retinal vascular abnormalities, independent of HT and kidney function.

Materials and methods

The study group included 39 adult individuals with ADPKD (15 males, 24 females), while the control group comprised 45 gender- and age-matched individuals (20 males, 25 females).

The following inclusion criteria were applied: the presence of cysts in both kidneys according to Ravine et al. criteria of the ADPKD phenotype [5], ADPKD in family history, serum creatinine concentration ≤1.35 mg/dL, and lack of developed DM. Individuals with a negative family history of ADPKD, an absence of cysts in the kidneys (Ravine's criteria not fulfilled), serum creatinine concentration ≤1.35 mg/dL, and no prior diagnosis of diabetes were enrolled for the control group.

Initially, both cohorts of patients qualified for prospective observation, according to the established inclusion criteria [28], as mentioned above. Since all examinations, including thorough ophthalmological examinations, were performed after 6 years of observation in both groups, at this time some of these initial inclusion criteria had already not been fulfilled. DM was not diagnosed in any patient from the ADPKD group, while it developed in five patients from the control group (DM type 2: four cases, DM type 1: one case; one patient treated exclusively with an anti-diabetic diet, two patients with oral anti-diabetic drugs, one with insulin therapy). The duration of diabetes at the time of the ophthalmological examination was approximately 2 years. Patients who developed DM were not excluded from the study due to its prospective, cohort nature, which requires monitoring of parameter changes in all patients in the study and control groups who met the specified inclusion criteria for the study at the beginning of the observation period. Additionally, the short duration of DM in these patients and its good control (HbA1C; 5.34 ± 0.56%) determine the low probability of developing diabetic retinopathy, the features of which were not found in the ophthalmological examination.

The study adhered to the tenets of the Declaration of Helsinki, and the study protocol was approved by the Local Research Bioethics Committee of the Pomeranian Medical University in Szczecin (decision BN-001/135/06). Each patient provided written informed consent for his/her involvement.

A full medical history review was obtained from the participants. The waist-hip ratio (WHR) was calculated as the proportion of the waist and hip circumferences, and the body mass index (BMI) was calculated as weight/height squared (kg/m2). The fasting venous blood sample of each participant was tested for glucose (the enzymatic-amperometric method (Cobas GLUC 800: 04,404,483,190 with a Super GL system, Diagnostic Systems, Germany)), insulin (microparticle enzyme immunoassay (Ax-Sym MEIA, Abbott Laboratories, Abbot Park, USA)), C-peptide (electrochemiluminescent method (Cobas 6000 system, Roche, Mannheim, Germany)), HbA1c (immunoturbidimetric method (Cobas HbA1c 150: 20753521322)). The measurements of serum creatinine, urea, uric acid, and lipid levels (total cholesterol (TC), LDL-cholesterol, HDL-cholesterol, triacylglycerol (TG)) were performed with a Bio-Autoanalyzer Cobas Integra 800 (Roche, Mannheim, Germany). Homeostatic model assessment (HOMA) indices of insulin action were analyzed. Insulin resistance in patients was expressed with the HOMA-% sensitivity (HOMA%S) formula, and pancreatic beta-cell function was expressed with the HOMA-% beta (HOMA%B) index [29]. The e-GFR was calculated from a single serum creatinine measurement with the chronic kidney disease epidemiology collaboration (CKD-EPI) equation [30].

Standard ophthalmological examination

A full ophthalmologic examination, including pupil reflexes, anterior segment and posterior segment, was performed in both eyes of 39 ADPKD patients and 45 healthy subjects. Visual acuity (VA) was evaluated before dilatation of the pupil. Fundus examination was performed using slit-lamp indirect ophthalmoscopy with noncontact slit-lamp lenses (90D double aspheric Volk lens; Shanghai, China) and normal fundus photography. The presence of the following abnormalities were noted and used to grade retinopathy: arteriolar narrowing or microaneurysms, arteriovenous crossings, retinal hemorrhages, cotton wool spots, exudates, and papilledema. Grading of the retinopathy was performed by an experienced ophthalmologist using the Keith-Wagener classification: Grade I – mild generalized retinal arteriolar narrowing or sclerosis; Grade II – definite focal narrowing and arteriovenous crossings, moderate-to-marked sclerosis of the retinal arterioles and exaggerated arterial light reflex; Grade III – retinal hemorrhages, exudates, and cotton wool spots, sclerosis and spastic lesions of the retinal arterioles; Grade IV – severe grade III and papilledema [22].

Intraocular pressure (IOP) measurement

The IOP was measured using a Pascal dynamic contour tonometer (DCT) (SMT Swiss Microtechnology AG, Port, Switzerland). Before the examination, topical anesthetic was instilled on the eye (Alcaine®; Alcon Laboratories Inc., Fort Worth, TX, USA). Additionally, the ocular pulse amplitude (OPA) and a quality score (Q) were presented with every measurement. The quality score ranges from Q1 to Q5, where Q1 and Q2 correspond to the most reliable results. Hence, only Q1 or Q2 results were included in the statistical analysis.

Accordingly, the actual arterial blood pressure (BP) was directly measured prior to ophthalmic examination in all subjects using a non-invasive blood pressure system with a manual aneroid manometer. The mean result from three measurements obtained with 5-minute resting intervals was calculated. A systolic/diastolic blood pressure ≥ 140/90 mmHg or the use of any anti-hypertensive drug qualified for the diagnosis of HT in the examined subjects. From the obtained BP data, the systemic mean arterial pressure (MAP) was calculated as follows: MAP = diastolic BP + 1/3 (systolic BP − diastolic BP) mmHg. Using the measured IOP and BP data for each examination session, the mean ocular perfusion pressure (MOPP) was analyzed as follows: MOPP = 2/3 × (MAP − IOP).

Retinal vessel analysis

Retinal vessel analysis (RVA) was performed in both eyes of 39 ADPKD patients and 45 healthy subjects. For static retinal vessel analysis (SVA), the FF450 plus fundus camera (Zeiss AG, Jena, Germany) was used, and 30° retinal photographs of each subject were collected and analyzed using VISUALIS and Vessel Map Software (IMEDOS Systems, Ltd, Jena, Germany), as described previously [31]. The standard parameters for this evaluation were as follows: central retinal arteriolar equivalent (CRAE), which relates to the diameter of the central retinal artery; central retinal venular equivalent (CRVE), which relates to the diameter of the central retinal vein; and AVR, which represents the CRAE/CRVE ratio.

The dynamic retinal vessel analysis (DVA) device and study protocol have been described elsewhere [32]. Briefly, in both eyes, mydriasis was induced using 0.5% tropicamide. After 20 minutes, DVA was conducted. The major temporal arterial and venous segments that were approximately 1.5 mm long were evaluated in each eye. The measurements were located 1 to 2 disc diameters from the optic disc. The selection criteria for the arterial and venous segment locations were as follows: no crossing or bifurcation in the measured segment, a curvature not exceeding 30°, a distance from the neighboring vessels of at least one vessel diameter, and sufficient contrast with the surrounding fundus. The standard program for flicker stimulation using DVA consisted of three consecutive optoelectronic flicker light cycles (12.5 Hz flicker frequency and 80-second observation each) and a total examination duration of 352 seconds. The response was measured as the difference between the mean vascular diameter for the last 10 seconds of flicker stimulation and the mean vascular diameter for the 30 seconds immediately preceding this flicker stimulation, divided by the latter value. The response was expressed as the mean of the calculations for the three flicker cycles. Only one artery and one vein were measured in each eye.

Statistical analysis

Since most of the analyzed quantitative parameters presented distributions significantly different from a normal distribution (Shapiro-Wilk test), the non-parametric Mann-Whitney U test was applied to compare values between groups, and the Spearman rank correlation coefficient (Rs) was used to measure the strength of the association between variables. Qualitative parameters were compared between groups with Fisher's exact test. Multivariable analysis of independent factors associated with retinal vessel parameters was performed with the general linear model (GLM). P < 0.05 was considered statistically significant. Statistical analysis was performed with Statistica 13 software.

Results

Both the ADPKD and control groups were comparable in terms of mean age (43.58 ± 11.6 vs 43.71 ± 9.1 years), gender distribution (36.8% vs 44.4% of males), and BMI. HT was observed more frequently in ADPKD patients, with both systolic blood pressure (SBP) and diastolic blood pressure (DBP) values significantly higher. The serum concentrations of creatinine, urea, and uric acid were significantly higher and the e-GFR was significantly lower in the ADPKD group than in the controls (Table 1). Fasting levels of the metabolic parameters (glucose, insulin, C-peptide, total cholesterol, HDL-cholesterol, LDL-cholesterol and triacylglycerol) were not significantly different between groups (Table 1).

Clinical and biochemical characteristics of the ADPKD and control groups. Data are presented as the mean ± SD (median) or number (percentage) of patients with a particular feature

Parameter ADPKD group (n=38) Control group (n=45) p-valuea
Age (years) 43.6 ± 11.6 (44) 43.71 ± 9.11(41) 0.87
Male gender (%) 14 (37%) 20 (44%) 0.51
BMI (kg/m2) 27.3 ± 5.3 (27.1) 25.7 ± 4.3 (25.4) 0.26
Hypertension 22 (67%) 7 (16%) <0.0001
SBP (mmHg) 135 ± 12.9 (132) 126±13.9 (125) 0.02
DBP (mmHg) 89 ± 9.34 (88) 82.6±10.7 (83.0) 0.018
MAP 104 ±9.043 (103.3) 97.04±10.9 (97) 0.006
TC (mg/dL) 219 ± 36.7 (222) 218 ±39.1 (212) 0.91
LDL (mg/dL) 133 ± 28.1 (129) 127 ± 37.4 (117.5) 0.26
HDL (mg/dL) 56.2 ± 11.5 (56) 58.02 ± 13.7 (58) 0.61
TG (mg/dL) 116 ± 56.4 (102) 120 ± 99.2 (97) 0.504
Fasting glucose (mg/dl) 92.6 ± 13.1 (89.5) 95.0 ± 13.6 (94) 0.22
Fasting insulin (μU/ml) 11 ± 10.5 (7.2) 12.1 ± 14.1 (7.9) 0.68
HbA1C (%) 5.2 ± 0.33 (5.2) 5.34 ± 0.56 (5.2) 0.77
HOMA%S 61.8 ± 40.3 (61.83) 69.6 ± 56.9 (53.65) 0.94
HOMA%B 132 ± 74.01 (109.4) 133 ± 115 (96) 0.26
Urea (mg/dL) 37.1 ± 16.9 (33.5) 28.2 ± 8.61 (27.5) 0.0078
Uric acid (mg/dL) 6.34 ± 1.94 (6.2) 5.43 ± 1.39 (5.35) 0.044
Creatinine (mg/dL) 1.084 ± 0.58 (0.97) 0.82 ± 0.12 (0.82) 0.00043
eGFRCKD EPI (mL/min/1.73m2) 81.3 ± 26.3 (84.05) 98.4 ± 11.6 (98.7) 0.002

Abbreviations: ADPKD, autosomal dominant polycystic kidney disease; BMI, body mass index; CKD EPI, Chronic Kidney Disease Epidemiology Collaboration equation; DBP, diastolic blood pressure; e-GFR, estimated glomerular filtration rate; HDL, high density lipoprotein cholesterol; HbA1C, hemoglobin A1C; HOMA%B, homeostasis model assessment % beta; HOMA%S, homeostasis model assessment % sensitivity; LDL, low-density lipoprotein cholesterol; SBP, systolic blood pressure; TC, total cholesterol; TG, triacylglycerols. Bold data represent significant differences.

ADPKD group vs the control group; Fisher exact test for qualitative variables; Mann-Whitney test for quantitative variables

Outstandingly, the severity of hypertensive retinopathy appeared to be more advanced in the ADPKD group than in the control group. According to Keith-Wegener classification, retinal arteriolar narrowing (Grade I) and arteriovenous crossing (Grade II) were significantly more common in the ADPKD group in comparison to controls (Table 2). Importantly, in both study groups, we did not find vascular abnormalities such as retinal hemorrhages, exudates, cotton wool spots, sclerosis, spastic lesions of the retinal arterioles, or papilledema, or microaneurysms, which are very characteristic of ADPKD patients in other vascular beds.

Grading of retinopathy in ADPKD patients and control group according to the Keith-Wagener classification

Group ADPKD group (n=73 eyes) Control group (n=90 eyes) p-value*
No retinopathy 32 (44%) 75 (83%) reference
Grade I (AN) 33 (45%) 12 (13%) <0.00001
Grade II (AVC) 8 (11%) 3 (3%) 0.0070

Fisher's exact test in comparison to “No retinopathy” group. Abbreviations: ADPKD, autosomal dominant polycystic kidney disease; AN, arteriolar narrowing; AVC, arteriovenous crossing

Table 3 provides the values of ocular together with macro-and micro-retinal vessel parameters obtained in both investigated groups of patients. We observed that the AVR values were considerably lower in ADPKD patients than in controls (p < 0.0001). No significant difference in arterial and venous responses to flicker stimulation was identified between the eyes from the ADPKD and control groups. There was no difference in the values of the IOP and OPA between the investigated groups. We observed that the MOPP values were significantly higher (p < 0.0001) in the ADPKD group than in the controls and correlated positively with SBP and DBP. Interestingly, the OPA measurements were strongly related to the MOPP values. An increase in the MOPP was associated with lower OPA values (Rs = −0.39, p = 0.004 in the ADPKD group and Rs = −0.26, p = 0.02 in the control group).

The values of ocular and macro- and micro-retinal vessel parameters in ADPKD patients and the control group

Parameter ADPKD group (n=76 eyes) Control group (n=90 eyes) p-value*
AVR 0.806 ± 0.064 (0.81) 0.876 ± 0.056 (0.88) < 0.00001*
DVA A [%] 3.32 ± 2.15 (3.3) 3.37 ± 2.00 (3.2) 0.78*
DVA V [%] 3.72 ± 2.18 (3.3) 4.31 ± 2.38 (4) 0.096*
IOP values (mmHg) 17.2 ± 2.27 (17.4) 17.8 ± 0.98 (17.7) 0.35*
OPA (mmHg) 2.71 ± 1.017 (2.5) 2.93 ± 0.97(2.75) 0.18*
MOPP (mmHg) 52.11 ± 6.25 (52.03) 46.77 ± 7.43 (46.77) < 0.0001*

Mann–Whitney test; Abbreviations: ADPKD, autosomal dominant polycystic kidney disease; AVR, arterio-venous ratio; IOP, intraocular pressure; DVA A, dynamic retinal vessel analysis of arteries; DVA V, dynamic retinal vessel of veins; MOPP, mean ocular perfusion pressure; OPA, ocular pulse amplitude. Bold data represent significant differences. Median value in parenthesis.

Significantly, the AVR measurements were dependent on the arterial blood pressure values. An increase in systolic blood pressure was associated with a lower AVR index (Rs = −0.25, p = 0.04 in the ADPKD group and Rs = −0.12, p = 0.29 in the control group). Similarly, diastolic blood pressure results correlated negatively with AVR values (Rs = −0.16, p = 0.20 in the ADPKD group and Rs = −0.25, p = 0.03 in the control group). Accordingly, the severity of hypertensive retinopathy according to the Keith-Wagener classification correlated positively with SBP values (Rs = +0.27, p = 0.03 in the ADPKD group and Rs = +0.27, p = 0.02 in the control group). Remarkably, the severity of hypertensive retinopathy positively correlated with participant age (Rs = +0,27; p = 0.02 in the ADPKD group and Rs = +0.28, p = 0.006 in the control group). A similar correlation was found in the ADPKD group between the arterial and venous responses to flicker stimulation and age (Rs = −0.35, p = 0.003 and Rs = −0.24, p = 0.045, respectively). This finding indicates that older patients have more advanced vascular changes than their younger counterparts.

Importantly, we also observed in univariate analysis that AVR values were lower in men than in women among controls (0.853 ± 0.051 vs 0.892 ± 0.054, p = 0.007) but not among ADPKD patients (0.804 ± 0.068 vs 0.808 ± 0.062, p = 0.84). The multivariate analysis of ADPKD patients and controls revealed that male gender was an independent factor significantly associated with lower AVR values (β = −0.171, p = 0.027). Finally, the multivariable analysis of ADPKD patients and controls (Table 4), adjusted for age, gender, e-GFR and the presence of HT, revealed that ADPKD was an independent factor associated with lower AVR values (by 0.069 on average, β = −0.50, p < 0.0001).

Multivariate analysis including AVR as dependent variable and group (ADPKD patients vs controls), age, gender, eGFR and presence of hypertension as independent variables

Independent variables Coefficient in regression equation Standardized beta p-value*
Group (ADPKD vs controls) −0.069 −0.502 <0.0001
Gender (male vs female) −0.24 −0.171 0.027
Age (years) 0.00056 0.083 0.37
Hypertension 0.0052 0.037 0.7
eGFRCKD EPI (mL/min/1.73m2) 0.0026 0.076 0.44

significance of each independent variable in the general linear model (GLM). Abbreviations: ADPKD, autosomal dominant polycystic kidney disease; AVR, arteriovenous ratio; eGFR: estimated glomerular filtration rate; CKD EPI, Chronic Kidney Disease Epidemiology Collaboration equation

Discussion

Hypertension, arterial vasospasm, and extensive remodeling of small renal arteries and arterioles at early stages of cystic kidney disease result in cardiovascular complications that form the leading cause of death in ADPKD [19]. Therefore, verifiable detection of vascular changes in retinal vessels seems to be an important diagnostic task in subjects suffering from ADPKD. The early detection of vascular retinopathy signs is an important step in the risk stratification of patients with this chronic incurable illness for medical purposes and suitable treatment onset. In the present work, our effort was devoted to analyzing in detail the retinal vessel quality in non-diabetic ADPKD patients using selected, highly objective ophthalmological tests and comparing it to that of non-ADPKD subjects.

The quantitative measurement of different retinal vessel metrics, including the AVR, permits the objective detection of retinal microvascular changes. The AVR quantifies the change in diameter of retinal blood vessels, and it is basically the ratio of arteriole to venule diameter [33, 34]. To our knowledge, this is the first study exploring retinal vessel caliber and function using the RVA method in ADPKD patients with preserved normal kidney function. Here, we showed that ADPKD was an independent factor associated with a lower AVR irrespective of age and the presence of HT. We found no retinal hemorrhages, cotton wool spots, exudates, or papilledema, or microaneurysms in ADPKD patients.

High blood pressure primarily affects the blood vessels in the retina, altering the vessel caliber. Several study groups documented low AVR values in the course of HT [25, 27]. Despite numerous studies quantifying retinal vessel caliber in HT and other cardiovascular diseases, only a few analyzed retinal vascular measurements and AVR in the course of chronic kidney disease (CKD). Accordingly, Liu et al. observed that the retinal arteriole diameter was narrower in patients with CKD and that a low retinal arterial caliber was significantly associated with a lower e-GFR [35]. Baumann et al. [24] documented lower AVR in CKD patients than in controls. The higher age of non-diabetic CKD patients and their higher SBP independently predicted a lower retinal arteriolar diameter [24]. Similarly, in our study, AVR measurements were lower in ADPKD and dependent on the SBP values. Interestingly, we observed that male sex was an independent factor associated with lower AVR values. Likewise, Ponto et al. also observed that men had a lower AVR than women, and the decrease in AVR values with increasing age was steeper in men than in women [27].

It was previously shown in Pkd2+/− mice, which are the orthologous animal model of ADPKD, that the resistance arteries in their bodies present with enhanced vasoconstriction and increased arterial remodeling [36, 37]. Both of these processes may also be responsible for the increased risk of diverse vascular complications reported in ADPKD patients. Importantly, in the retinal microvasculature, we did not find microaneurysms, which are common in other vascular beds in ADPKD patients [20]. We hypothesize that mutations of either the PKD1 or PKD2 gene, encoding polycystins responsible for ADPKD, may participate in the mechanism leading to a decrease in AVR value through abnormalities of intracellular calcium ion (Ca2+) metabolism. Changes in the tone of the retinal arterioles are primarily achieved through changes in [Ca2+] within the smooth muscles of these vessels, which regulate muscle cell contraction and, subsequently, vascular constriction. Vascular smooth muscle cell (VSMC) contraction can be evoked by an increase in cytosolic [Ca2+] owing to transmembrane Ca2+ influx or sarcoplasmic reticulum (SR) Ca2+ release. Ca2+ influx across the plasma membrane can occur via a variety of Ca2+ channels, including voltage-gated, store-operated, and ligand-gated channels [38]. Ca2+ may also be released from intracellular stores via RyR- or IP3-R-gated channels in the SR membrane. Using high-speed confocal Ca2+ imaging, it has been demonstrated that the resulting signals are far from homogeneous, with spontaneous activity in retinal arterioles being characterized by both localized Ca2+ sparks and more global Ca2+ waves and oscillations [39, 40, 41]. PKD1 and PKD2 gene products (PC-1 and PC-2 proteins, respectively) form a subgroup of the transient receptor potential (TRP) superfamily, which consists of a large number of nonselective cation channels with variable degrees of Ca2+ permeability [42]. Recently, Yanda et al. [43] found that several key components of Ca2+ signaling are elevated in mouse PN (PC1 null) vs PH (PC1 containing) cells and proposed that elevated Ca2+ release from the SR is actually the key factor stimulating renal cyst growth. Qi Qian et al. [44], using an in vitro model, found decreased PC-2 expression in pkd2+/− vessels, roughly half of the wild-type level. Consistent with these observations, freshly isolated pkd2+/− VSMCs have significantly altered intracellular Ca2+ homeostasis. The resting [Ca2+]j was approximately 17% lower in pkd2+/− cells than in wild-type cells (p=0.0003), and the total SR Ca2+ stores were significantly decreased (p<0.0001). Pkd2+/− VSMCs have decreased resting [Ca2+] j and capacity of the SR Ca2+ store. PC-2 not only conducts Ca2+ from SR stores but is also intimately related to cytosolic Ca2+ levels, as they the open probability of PC-2. Low levels of Ca2+ (up to 1 μM) increase the open probability of PC-2, whereas high levels (>1 μM) are inhibitory, ultimately giving PC-2 a bell-shaped Ca2+ response [45]. The PC-2/PC-1 complex is important in maintaining proper signaling throughout the cell, thus explaining the requirement for both PCs in maintaining calcium homeostasis and how gene mutation in either polycystin can distinctly affect cell function. Interestingly, in our previous study [46], we found that ADPKD patients with preserved normal kidney function had higher Ca2+ concentrations in serum and erythrocytes than non-ADPKD controls, indicating the potential role of the polycystin complex as a putative membrane-based calcium channel and regulator of calcium homeostasis in different types of cells and in the retinal vasculature. This might also indicate that the natural course of ADPKD leads to disorders of intra- and extracellular calcium metabolism preceding the onset of renal failure. Based on our previous molecular observations in ADPKD patients, the results of our current study may indicate that dysfunction of the PC-1 and PC-2 in the SR membrane and in the cellular membrane, caused by mutation of PKD1 or PKD2 gene, interferes with Ca2+ flow through these membranes, leading to anomalous Ca2+ homeostasis, resulting in arteriole contraction, perhaps also in the human retina. In addition, Coban et al. showed that in patients with advanced stages of ADPKD, the arterial stiffness (AS) development, which contributes to endothelial dysfunction, was increased compared to patients at earlier stages or to healthy individuals [47]. Accordingly, results of Choi et al. suggest that the changes of AS in ADPKD patients may be caused by aberrant Ca2+ homeostasis [48].

On the other hand, inhibition of the endogenous glutamate receptor-dependent signal transduction cascade in the Müller cells of PKD21/703 transgenic rats with mutated polycystin-2 or pharmacological inhibition of purinergic P2Y1 and adenosine A1 receptors in Müller cells of wild-type retinas, results in swelling of these cells under hypo-osmotic conditions. Abrogation of osmotic-related adenosine-triphosphate (ATP) release through the glutamate signaling pathway might be glioprotective; that is, it may avoid cytotoxic Ca2+ overload due to overstimulation of P2Y1 receptors [49], prevent excessive release of different growth factors from the cells [50], or be neuroprotective through the upregulation of NTPDase1 in retinal Müller cells [15]. However, the loss of osmotic ATP release from Müller cells may also contribute to the development of cytotoxic retinal vasculature edema in PKD21/703 rats [15], affecting vessel caliber. Notwithstanding, further research is essential to determine the molecular mechanisms of osmotic ATP release from Müller cells and calcium metabolism in the retinal cells of transgenic animal models with polycystic kidney disease due to PC mutations.

Study limitations

Our study provides interesting results; it does not, however, lack drawbacks. The main limitation of our study is the rather low number of patients in the study group. This is associated with the rare occurrence of ADPKD in the Caucasian population (1:400–1:1000). Another factor contributing to the small size of the study group is the inclusion of patients with normal kidney function in the study – given that kidney failure is an element of ADPKD, this inclusion criterion thus affects the number of patients in the study group.

Conclusion

Overall, we suggest that a lower AVR value found in the retinal microcirculation, independent of HT, could be a specific pathophysiological ocular manifestation of the systemic vasculopathy that develops in the course of ADPKD. Increased awareness of retinal vascular symptoms and signs in ADPKD patients may provide an earlier diagnosis of retinal dysfunction and subsequent treatment before irreversible vision defects develop in the eyes of ADPKD patients.

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