Variation in the Dopamine-4-Receptor Gene in Patients with Type 1 Diabetes Open Access

Dopamine (DA), a catecholaminergic neurotransmitter present in central and peripheral tissues, is crucial for many processes and functions including cognition, sleep, memory as well as blood pressure, glucose homeostasis, hormone regulation, and lipid metabolism [1, 2]. DA also has prominent effects in the immune system, affecting B and T lymphocytes, monocytes/macrophages, dendritic cells, eosinophils, neutrophils, and NK cells [3]. Moreover, some immune cells are able to synthesize DA and release it upon specific stimuli, suggesting that DA is a bidirectional mediator between nervous and immune cells [4]. The effect of DA is mediated by binding to dopamine receptors (DRs), classified into two subfamilies as follows: the D1-like receptor family (D1R and D5R), which stimulates cyclic adenosine monophosphate production, and D2-like receptor family (D2R, D3R, and D4R) that decreases cyclic adenosine monophosphate levels [5].

The DA D4 receptor, encoded by the DRD4 gene, is associated with attention-deficit hyperactivity disorder, schizophrenia, novelty-seeking personality trait and risk-taking behavior, alcoholism, mood disorders, as well as autoimmunity and (as such) is a target for numerous antipsychotic drugs [6, 8]. One of the most studied polymorphisms of the DRD4 gene is a cytosine (C) to thymine (T) transition at base −521 in the upstream promoter region (−521C>T). The C allele was once described as associated with a 40% increase in DRD4 transcription [9]; however, these results were not reproduced in two independent studies [10, 11]. Previous studies have explored the role of −521C>T DRD4 gene polymorphism in neurocognitive and psychiatric disorders but little is known about the relations between this polymorphism and other clinical conditions. Epidemiological studies also corroborate the evidence of a connection between diabetes and neurodegenerative disorders as well as mood disorders [12, 13].

As genetic variant of DRD4 polymorphism may modify DA neurotransmission, it is likely to also have an impact on the risk of T1D and/or its comorbidities. The aim of this novel genetic association study was to investigate whether the −521C>T DRD4 gene polymorphism may affect diabetes mellitus type 1 (DM1) and its comorbidities.

This study was conducted on 400 Caucasoid adolescents including 199 boys and 201 girls with clinical and laboratory diagnosis of DM1, recruited from the Chair and Clinics of Pediatrics, Diabetology and Endocrinology, Medical University of Gdańsk. DM1 diagnosis was based on the American Diabetes Association criteria [14]. There was no evidence for MODY or other rare forms of insulin-deficient diabetes. All patients were treated with humanized insulin at doses of 0.87 ± 0.2 U/kg. At the time of sample collection, biochemical measurement of renal function, C-reactive protein (CRP), glycated hemoglobin, as well as lipid levels (total cholesterol [TC], triglycerides [TG], high-density lipoprotein cholesterol [HDL], low-density lipoprotein cholesterol [LDL]) were monitored. Complete physical examination, anthropometry, and examination for any associated conditions or complications were routinely done for every patient. All subjects with diabetes-related complications were newly diagnosed and previously untreated.

Control group consisted of 300 healthy volunteers including 154 boys and 146 girls from the same population. Neither signs of autoimmune and/or inflammatory disease at the time of sampling nor evidence of DM1 in families were disclosed as confirmed by medical records and laboratory tests.

Written informed consent to participate in the study was obtained from all subjects or from their parents. This study was approved by the Ethics Committee of the Medical University of Gdańsk (NKEBN/2014/2009), and the investigation was carried out in accordance with the principles of the Declaration of Helsinki.

Systolic and diastolic blood pressures were measured using automatic 24-h ambulatory blood pressure monitoring by the Holter method. All the average values of the blood pressure were expressed in the centile charts. Arterial hypertension was diagnosed when the blood pressure value reached at least 95th percentile for the corresponding age, gender, and height on at least three separate occasions [15].

Ophthalmologic investigation was performed in all DM1 patients. Diabetic retinopathy was determined by visual acuity, intraocular pressure measurement, anterior segment estimation by slit lamp (Topcon SL-82, Japan), and fluorescein angiography (digital camera-Topcon IMAGEnet 2000, Japan). The eye fundus examination was performed with the +90D lens (Ocular Instruments Inc., Bellevue, WA, USA). Each image was graded for retinopathy according to the Early Treatment for Diabetic Retinopathy Study (ETDRS) severity level and was dichotomized as having retinopathy (level 15 and above) or not having retinopathy (≤14) [16]. Renal function was determined by estimated glomerular filtration rate (eGFR), which was evaluated by using the Zappitelli equation: eGFR (mL/min/1.73 m²) =  {507.76 × e^[0.3 × ^{height (cm)]}}/[serum cystatin C (mg/L)^0.635 × serum creatinine (μmol/L)^0.547] [17].

The urinary albumin excretion was expressed as the average of three 24 h collections. Cases were classified as microalbuminuria when in at least two out of three urine samples, urinary albumin excretion ratio was >30–300 mg/24 h. Diabetic nephropathy was defined as persistent microalbuminuria in two out of three consecutive urine samples without clinical or laboratory evidence of other kidney or urinary tract disease.

Dyslipidemia was defined by the presence of one or more abnormal serum lipid concentrations: TC ≥5.17 mmol/L (200 mg/dL); HDL <1.03 mmol/L (40 mg/dL); LDL ≥2.6 mmol/L (100 mg/dL); TG ≥1.69 mmol/L (150 mg/dL) [18]. Further analyses were performed after controlling for age and pubertal stage to avoid differences in lipid values [19].

Venous blood samples were withdrawn after 12–14 h overnight fasting. Serum and plasma samples were collected from DM1 patients by centrifugation at 500 g for 15 min and stored at −80°C until analysis.

Plasma TC, TG, and HDL concentrations were measured in an independent, ISO-certified laboratory. LDL was estimated by the Friedewald equation [20]. Concentrations of TNF-α, IL-6, IL-10, ICAM-1, and VEGF-A were determined using commercially available enzyme-linked immunosorbent assay kits (R&D Systems, USA) according to the manufacturer’s protocol.

Genomic DNA from all subjects was isolated from EDTA-stabilized blood using the EXTRACTME DNA BLOOD KIT (BLIRT, Poland). DNA was stored at −20°C until the time of use.

The genotyping of −521C>T DRD4 gene polymorphism (rs1800955) was carried out using tetra-primer amplification refractory mutation system-polymerase chain reaction. In this assay, confronting pairs of primers (outers and inners) were used as shown below:

• forward outer: 5′ – CCC​CTG​CCC​AGG​GTC​AGA​GGG​GCG​CCT​A – 3′

• reverse outer: 5′ – CAT​CGA​CGC​CAG​CGC​CAT​CCT​ACC​CGG​C – 3′

• forward inner: 5′ – GGG​CAG​GGG​GAG​CGG​GCG​TGG​AGT​GT – 3′

• reverse inner: 5′ – CGC​GGA​CTC​GCC​TCG​ACC​TCG​TGC​TCG – 3′.

The region containing −521C>T DRD4 gene polymorphism was amplified in a total volume of 15 μL, containing 20 ng of DNA template, 3.3 mm MgCl₂ (BLIRT, Poland), 200 μm dNTP (BLIRT, Poland), 250 nm of each primer (Sigma-Aldrich, USA), and 0.75 U FIREPol DNA Polymerase with 1x buffer (Solis BioDyne, Estonia). The procedure consisted of denaturation at 96°C for 12 min, followed by 35 cycles of 96°C for 30 s, 70°C for 30 s, 72°C for 30 s, and a final extension at 72°C for 5 min. PCR products were visualized on a 2% agarose gel with ethidium bromide staining. Genotyping was performed as follows: 448, 297 bp for CC genotype; 448, 297, 204 bp CT genotype; and 448, 204 bp TT genotype. DNA samples were first sequenced to establish three DRD4 gene polymorphic variants as a quality control. Afterward, DNA samples of the CC, CT, and TT individuals were routinely added to the examined ones to ensure genotype accuracy.

Percentages of CD14⁺⁺CD16⁻ and CD14⁺CD16⁺ monocytes in the peripheral blood of all subjects were evaluated using flow cytometry. 50 μL aliquots of fresh venous blood were stained with anti-CD14 (IgG2b mouse PerCP, clone MφP9; BD Biosciences, USA) and anti-CD16 (IgG2 mouse APC-Cy7, clone 3G8, BD Biosciences, USA) monoclonal antibodies. The samples were incubated for 30 min in the dark, followed by lysis with IMMUNOPREP Reagents (ImmunoTech, USA). Cells stained with isotype-identical nonspecific antibodies served as a negative control.

Expression of surface markers was assessed using LSRII flow cytometer (BD Biosciences, USA), and obtained data were analyzed using FACSDiva 6.0 Software (BD Biosciences, USA). Monocytes were gated according to their forward and side scatter characteristics. Typically, 10,000 events were acquired in this region. The monocyte subsets were identified based on the expression of the CD14 and CD16 surface markers.

The results were analyzed using Statistica, version 12 (StatSoft, Inc., USA). Conformation of the allele frequencies to the Hardy-Weinberg equilibrium proportions was tested by the χ² test. The genotypes and allele frequencies of the −521C>T DRD4 gene polymorphism were compared using Pearson’s χ² test. Differences between groups were analyzed by ANOVA for normally distributed values or the Kruskal-Wallis test for nonparametric values and by the χ² Pearson test for dichotomous variables. To deal with multiple testing, Benjamini-Hochberg’s correction was used for statistical significance. The study’s power was calculated post hoc using the Genetic Association Study (GAS) Power Calculator online tool based on the algorithm from the CaTS power calculator for association studies [21]. Based on the observed prevalence of the −521C>T DRD4 gene polymorphism in our population, this study had more than 80% power to detect a relative risk of DM1 as well as its complications between carriers and noncarriers with a significance of p = 0.05. Logistic regression model was used to examine the association between −521C>T DRD4 gene polymorphism and diabetes-related complications and comorbidities. The level of significance was set at p ≤ 0.05.

The −521C>T DRD4 genotypes were analyzed in DM1 patients and healthy controls. The occurrence of each genotype and allele frequencies is shown in Table 1. The genotype distributions (for both healthy group and DM1 patients) were in Hardy-Weinberg equilibrium (p = 0.36 and 0.92, respectively). Based on the observed prevalence of DRD4 polymorphism in our population, this study had more than 99% power to detect a relative risk of DM1 between genotypes with a significance of p = 0.05. Comparison of the frequencies of −521C>T DRD4 genotypes between healthy group and the DM1 patients revealed significant differences (p = 0.01). The presence of CC variant was connected with a nearly two-fold reduced risk of DM1 (OR = 0.539, p = 0.005), while the TT genotype was associated with increased risk of this condition (OR = 1.408, p = 0.04). In case of the allele frequencies within groups, significant differences were also found (p = 0.003) – the C allele is associated with lower risk of DM1 (OR = 0.725).

Characteristics of DM1 patients differing in the −521C>T DRD4 polymorphism are shown in Table 2. There were no statistically significant differences in sex, age, BMI, glycated hemoglobin concentration, as well as systolic and diastolic blood pressure between subjects with different DRD genotypes. However, we have noticed that C carriers had higher age of diabetes onset and lower duration of the disease when compared with T-bearing patients (p = 0.04 in both cases). Simultaneously, individuals with TT variant and T allele had the lowest values of eGFR (p = 1*10⁻⁴ and p = 4*10⁻⁴, respectively).

We compared the distribution of genotypes and alleles between individuals with and without DM1 comorbidities. There were no differences in the genotypic and allelic distributions with respect to nephropathy (p = 0.09 and 0.07, respectively) and hypertension (p = 0.38 and 0.78, respectively). Nevertheless, we observed alterations in the frequencies of the −521C>T DRD4 genotypes, but not alleles, due to diabetic retinopathy. Genotype distribution in patients with retinopathy was different in comparison to comorbidities-free group (p = 0.003). We also found variations in the genotypic and allelic distributions with respect to dyslipidemia (p = 0.004 in both cases).

Among significantly different variables reported in Table 3, the logistic regression model was performed. Table 4 shows the results of DRD4 genotype and allele interaction effects for retinopathy and dyslipidemia. No significant interaction effect of genotype was observed for nephropathy and hypertension (data not shown).

Logistic regression analysis revealed association of the CC variant with retinopathy (OR = 2.111, p = 0.01) and dyslipidemia (OR = 2.376, p = 0.001) with the genotype increasing the risk of both conditions. Furthermore, CT variant was connected with lower risk of retinopathy (OR = 0.441, p = 0.002). Logistic regression analysis also revealed a significant association between C allele and dyslipidemia (OR = 1.517, p = 0.004) with this variant being a risk factor for the condition.

Table 5 describes the association between −521C>T DRD4 polymorphism and serum concentrations of different variables in DM1 patients. There was no statistically significant difference in serum concentrations of CRP, IL-10, and TC between subjects with different CRP genotypes and alleles. However, CC carriers had the highest concentrations of ICAM-1 (p = 2*10⁻⁶), VEGF-A (p = 1*10⁻⁹), IL-6/IL-10 ratio (p = 0.01) as well as TG (p = 3*10⁻⁶) and the lowest concentration of HDL-C (p = 1*10⁻⁴). Simultaneously, concentration of TNF-α (p = 0.04), IL-6 (p = 7*10⁻⁴), and LDL-C (p = 9*10⁻⁴) did differ between variants of DRD4 gene. There were also considerable differences between the alleles. C carriers had the lowest concentrations of TNF-α (p = 0.04) as well as IL-6 (p = 0.02) and the highest concentrations of ICAM-1 (p = 4*10⁻⁷), VEGF-A (p = 2*10⁻⁸), LDL-C (p = 0.01), and TG (p = 0.01).

By means of flow cytometry, we identified two monocyte subsets in DM1 patients as follows: the CD14⁺⁺CD16⁻ and CD14⁺CD16⁺ cells (Table 6). Analyzing the ratios of monocytes, within peripheral blood mononuclear cells, CC genotype and C allele carriers had the lowest frequency of CD14⁺⁺CD16⁻ cells (p = 2*10⁻⁴ and 0.04, respectively) and the highest frequency of CD14⁺CD16⁺ monocytes (p = 1*10⁻⁴ and 0.04, respectively).

Dopaminergic pathways are one of the regulators of autoimmune reactions [7], with D2-like receptors playing a role in diabetes [22]. Therefore, we have investigated the association between the −521C>T DRD4 gene polymorphism and the risk of DM1 and its comorbidities. The key results of our approach are as follows:

1. 1.

   CC genotype and C allele are associated with a reduced risk of DM1, whereas TT genotype and T allele are associated with increased risk of DM1;

2. 2.

   CC genotype is associated with a higher risk of dyslipidemia and retinopathy in diabetic patients;

3. 3.

   CC genotype and C allele carriers had the highest frequency of pro-inflammatory CD16⁺ monocytes;

4. 4.

   the DRD4 −521C>T polymorphism modifies the inflammatory status as well as lipid profile in DM1 patients.

This study is the first attempt to assess the associations between DRD4 −521C>T polymorphism and DM1 prevalence. We have observed that the incidence of CC genotype is lower in DM1 patients in comparison to healthy group – the presence of CC variant was connected with a nearly two-fold decreased risk of DM1, while the risk of the disease for the carriers of the TT variant was one and a half times higher than for noncarriers. With regard to allele frequencies among study groups, significant differences were also found – T variant subjects had 1.4-fold higher risk of DM1 compared with the C carriers. In light of these findings, presence of the CC genotype and C allele is beneficial when it comes to DM1 development. Recent research showed that D2-like receptors are expressed peripherally in tissues critical for metabolic regulation, including insulin-secreting pancreatic β-cells, where they function as negative regulators of glucose-stimulated insulin secretion [23]. Moreover, insulin biosynthesis depends on the concentration of DA [24]. Regulatory mechanism that may, at least partially, explain the effects of DA involves a dopaminergic negative feedback loop. In this model, DA is cosecreted with insulin and acts in an autocrine/paracrine manner on insulin-secreting β-cells that express D2-like receptors [25].

In our study, we have also found significant differences in the frequencies of DRD4 genotypes and alleles in patients with DM1 comorbidities in comparison to complication-free group. We have observed that the incidence of CC variant is higher in a group with diabetic retinopathy in comparison to complication-free patients. The risk of retinopathy for CC genotype carriers was over two-fold higher than for noncarriers. Retinal DA directly modulates multiple aspects of light-adapted vision [26]. Animal model studies revealed that DA deficiency is the underlying mechanism responsible for early, DM1-induced visual dysfunction observed in diabetic retinopathy [27]. The DA D4 receptor gene expression is observed in all retinal layers [28], and D4R agonists improve retinal and visual functions [27]. DA can also inhibit VEGF-A-mediated angiogenesis by acting through its D2-like receptors present in the endothelial cells and their progenitors [29]. However, although endothelial cells express D4R, its effect on endothelial dysfunction in diabetes is still unknown.

Our study provides additional important observation – DRD4 −521C>T polymorphism alters lipid profile in DM1 patients and affects the probability of developing dyslipidemia for CC genotype and C allele carriers – such risks were near 2.5- and 1.5-fold higher, respectively, than for noncarriers. Dopaminergic signals are involved in the homeostatic regulation of lipid metabolism. Plasma TG potentially affect DA signaling as abundance of defective D2-like receptors and impaired signaling have been repeatedly associated with hypertriglyceridemic conditions such as obesity [30]. Binding DA to D2-like receptors is diminished in the brains of obese individuals, and activation of this receptor ameliorates circulating lipid profiles [31]. Moreover, numerous studies have demonstrated that the D2-like receptor agonist bromocriptine significantly reduces TG and free fatty acid concentrations [32].

Chronic low-grade inflammation and activation of the immune system as well as increased expression of cell adhesion molecules and proangiogenic factors have been implicated in the pathogenesis of DM1 and its comorbidities [33]. Our data imply various effects of DRD4 −521C>T polymorphism on the inflammatory status of DM1 patients. On one hand, CC genotype and C allele carriers have the lowest concentrations of TNF-α; on the other hand, these individuals have the highest concentrations of ICAM-1, VEGF-A, and IL-6 as well as IL-6/IL-10 ratio. Therefore, CC genotype and C allele are probably less beneficial than their CT/TT counterparts. The ability of DA to modulate immune responses by influencing the expression of adhesion molecules as well as cytokine and chemokine production is worth investigating in diseases where inflammatory component plays an important role, such as DM1 [34]. Moreover, it is worth noting that enhanced inflammatory response may be due to the fact that DA impairs the stability and function of regulatory T lymphocytes, which suppress profound inflammation [35, 36].

By the means of flow cytometry, we have identified two monocyte subsets in DM1 patients – CD14⁺⁺CD16⁻ classical and CD14⁺CD16⁺ nonclassical cells. We have found that CC genotype and C allele carriers had higher frequencies of nonclassical monocytes and lower percentages of classical cells when compared to their CT/TT counterparts. The CD16⁺ monocytes, described as pro-inflammatory population [37] and main producers of TNF-α [38], are known to be involved in pathogenesis of autoimmune disorders [39] and most likely play an important role in promoting inflammatory responses in DM1 [40, 41]. There are several reports about the effects of DA on monocytes – the hormone promotes CD16⁺ monocytes movement and adhesion [42] and its DRD4 receptor is being expressed by resting peripheral blood monocytes [43]. Thus, DA as well as DRs modulate monocyte functions [44].

The results of this investigation need to be considered in regards to the study’s strengths and limitations. First, though we were able to detect significant effects of a single polymorphism and our study has sufficient statistical power, the sample size in our analysis is relatively small. Simultaneously, the inclusion of a pure Caucasoid population from the northern region of Poland reduced heterogeneity and increased statistical power. Second, pediatric population with DM1 eliminates potentially confounding factors in adults such as cardiovascular diseases, hypertension, smoking, or alcohol consumption. Third, despite having detected DRD4 genotype-based differences that affect the development of DM1 and its comorbidities, there are still many unmeasured genetic and environmental factors that influence these associations. Therefore, conducting further studies on a larger group especially with the consideration of its genetic substructure is needed to confirm our results. In spite of the limitations, our findings emphasize the role of the −521C>T DRD4 gene polymorphism in patients with DM1.

In conclusion, we describe for the first time an association between the −521C>T DRD4 gene polymorphism and DM1 as well as its comorbidities. The most interesting finding is that the CC genotype protects against the development of DM1 and increases the risk of dyslipidemia and retinopathy in patients with already developed disease, suggesting importance of dopaminergic signaling pathways in the etiology of DM1 as well as its comorbidities. Moreover, DRD4gene polymorphism itself may be not only indirectly associated with dyslipidemia and/or retinopathy development by T1D promote, it can also be directly involved in these complications’ progression. Although our results are promising and may be useful in identifying individuals prone to develop DM1 and its comorbidities, they should be considered as preliminary and replicated on a larger cohort of subjects. Moreover, functional studies are required to investigate whether and how DRD4 gene influences the pathogenesis of DM1 and disease-related comorbidities.

This work was supported by The State Committee for Scientific Research ST49 (Medical University of Gdańsk).

Written informed consent to participate in the study was obtained from the subjects’ parent/legal guardian/next of kin. This study was approved by the Ethics Committee of the Medical University of Gdańsk (NKEBN/2014/2009), and the investigation was carried out in accordance with the principles of the Declaration of Helsinki.

The authors declare that they have no conflict of interest.

This research received no funding.

Bartosz Słomiński: major part of the experiment, wrote the manuscript, and data interpretation; Maria Skrzypkowska: critically reviewing and editing of the manuscript; Małgorzata Myśliwiec: diagnosed the patients and provided blood samples; and Piotr Trzonkowski: data interpretation. All authors reviewed the manuscript and all of them approved the final version.

All data generated or analyzed during this study are included in this article. Further inquiries can be directed to the corresponding author.