CD36 fatty-acid-transporter gene variants-CD36 G/A (rs1761667) and CD36 C/T (rs75326924) as biomarkers for risk-prediction in gestational diabetes mellitus

Abstract

BACKGROUND

Gestational diabetes mellitus (GDM) is a metabolic disorder causing hyperglycemia during pregnancy. Insulin resistance and decreased insulin secretion are linked to altered lipid metabolism that leads to progression of GDM. CD36 is a membrane glycoprotein involved in lipid metabolism and insulin sensitivity. Studies indicate that the CD36 gene is substantially linked to type 2 diabetes mellitus (T2DM) and could also influence GDM susceptibility. Insulin resistance and decreased insulin secretion are the hallmarks of T2DM, which is thought to have a similar genetic pathophysiology in GDM.

AIM

To investigate the impact of CD36 gene polymorphisms [rs1761667 (G/A) and rs75326924 (C/T)] and mRNA expression in GDM women.

METHODS

The case-control study involved a total of 400 pregnant women, (200 healthy controls and 200 GDM cases). The study of CD36 gene polymorphisms G/A (rs1761667) and C/T (rs75326924)) were determined by polymerase chain reaction-restriction fragment length polymorphism. The mRNA expression study of CD36 gene was analyzed by quantitative polymerase chain reaction/quantitative real-time polymerase chain reaction followed by statistical analysis done using GraphPad Prism8 software (ver. 8.0).

RESULTS

The study revealed statistically significant association (P < 0.05) in anthropometric/biochemical parameters (age, gestational age, body mass index, fasting prandial glucose, post-prandial glucose, triglyceride, low-density lipoprotein) between GDM cases and healthy controls. CD36 G/A(rs1761667) and CD36 C/T (rs75326924) polymorphisms were significantly associated with GDM cases. The heterozygous genotypes (GA and CT) of both variants showed significant association (P = 0.0001 and P = 0.0025, odds ratio = 2.683 and 2.022 respectively). Allele frequency of ‘T’ allele in CD36 C/T (rs75326924) polymorphism was also found to be significant (P = 0.0046). CD36 gene was upregulated in individuals with GDM as compared to healthy controls (P = 0.0001). However, the upregulation of gene expression was not significantly associated with the genotypes of CD36 G/A (rs1761667) and CD36 C/T (rs75326924) polymorphisms.

CONCLUSION

Heterozygous genotypes GA and CT of CD36 gene variants and expression are linked to GDM, potentially serving as predictive biomarkers for GDM susceptibility; further exploration needed in diverse ethnic communities.

Key Words: Association; Cluster of differentiation; Gene expression; Gene variants; Gestational diabetes mellitus; Polymerase chain reaction-restriction fragment length polymorphism

Core Tip: Gestational diabetes mellitus (GDM) is a metabolic disorder causing hyperglycemia during pregnancy. GDM is associated with adverse feto-maternal outcomes, type-2-diabetes mellitus (T2DM), GDM-recurrence, future obesity. Insulin-resistance is a physiological trait associated with progressing pregnancy that provides an adequate nutritional supply for the mother and fetus. Disruptions in this mechanism might facilitate onset of GDM. CD36-transmembrane glycoprotein receptor, contributes to fatty-acid absorption. Genetic alterations in CD36 gene can modulate expression of genes along these pathways to mitigate the diabetic effect during pregnancy. The integration of genotyping-expression studies will be crucial for advancing investigation in GDM treatment.

INTRODUCTION

Gestational diabetes mellitus (GDM) is characterised by hyperglycemia that occurs or is initially diagnosed during pregnancy. Globally, GDM affects between 14% to 16% of pregnancies[1,2]. The incidence differs based on various risk factors and screening strategies GDM is linked to detrimental feto-maternal outcomes, such as preeclampsia, cardiovascular metabolic disease, type 2 diabetes mellitus (T2DM), recurrence of GDM, and a heightened risk for later-life overweight[3-5]. The relationship between environmental factors and genetic predispositions may potentially affect the onset of GDM[6].

The prevalence of GDM among pregnant women in India ranges from 9% to 16% and varies throughout the five geographical zones of the country. The northern region had the greatest instances of GDM, followed by south India. Regions with low incidence include the western, central, and eastern zones[7]. In early pregnancy, 30% to 70% of diagnosed cases are categorised as GDM, stated by hyperglycemia occurring prior to 20 weeks of gestation. Early pregnancy outcomes are more serious than those of women with late gestational diabetes (hyperglycemia between 24 weeks and 28 weeks)[2].

Insulin resistance is a physiological trait associated with progressing pregnancy that provides an adequate nutritional supply for the mother and fetus. Disruptions in this mechanism might facilitate the onset of GDM[8]. It is widely recognized that GDM and T2DM have the same susceptibility and pathophysiology, defined by insulin resistance and altered insulin secretion[9,10]. A wide variety of research has established a substantial association between CD36 (cluster of differentiation 36) and T2DM at two distinct stages: Insulin resistance[11] and pancreatic β-cell dysfunction and damage[12,13].

CD36 is a 36kb transmembrane glycoprotein classified as a class B scavenger receptor, positioned at 7q11.2, and is expressed on the surface of various cell types[14]. CD36 contributes to fatty acid absorption, and multiple studies demonstrate correlations between increased CD36 expression in various tissues and insulin resistance[15]. A malfunction of CD36 receptors results in an imbalance in lipid metabolism and insulin resistance[16]. Modified lipoproteins and fatty acid uptake, lipid deposition and lipotoxicity, insulin response changes, energy substrate utilization, oxidative stress, inflammation, apoptosis, and fibrosis all contribute to the detrimental effects of CD36 signaling, which ultimately result in progressive and frequently irreversible organ dysfunction. CD36 is an essential component in the development of diabetes and associated consequences, making it a promising therapeutic target[13].

Genetic and environmental factors affect disease onset and development, and may significantly contribute to the pathophysiology of diabetes and its consequences. The evaluation of the impacts of genetic variability on CD36 gene expression during GDM seems fascinating. Due to the modifier role of CD36 gene in human metabolism and its association with T2DM, this study investigated whether two CD36 gene single nucleotide polymorphisms (SNPs) and its mRNA expression were linked to GDM in north Indian women[17,18].

MATERIALS AND METHODS

Selection of research subjects

This case-control study was done with ethical approval from the Institutional Ethical Committee (No 101st ECM II A/P18 dated May 18, 2020) at King George’s Medical University (KGMU), Lucknow, India, following the acquisition of signed informed consent from all participants. Patients were selected by experienced medical professionals based on the oral glucose tolerance test results and in accordance with the established Diabetes in Pregnancy Study Group India inclusion and exclusion criteria were used to recruit healthy pregnant women (controls) and GDM patients (cases) from the outpatient department of the Department of Obstetrics and Gynaecology at KGMU, Lucknow[19]. The study had 400 subjects, with 200 designated as controls and 200 as cases. Initially, 100 healthy control participants were genotyped to ascertain the Minor Allele Frequency of each SNP within the research population. The sample size was determined utilizing QUANTO software (version 3.0).

Clinical evaluation and sample collection

Anthropological data, including age, body mass index (BMI), gestational age, systolic and diastolic blood pressure, have been collected[20]. Expert medical professionals collected five millilitres of venous blood from the subjects, three millilitres in EDTA-coated vials for DNA extraction and two millilitres in plain vials for serum analysis to evaluate biochemical parameters[18,20]. Serum was extracted by centrifugation at 3000 RPM for 5-10 minutes and stored at -20 ºC. Using the Spectra Blood Analyser (Merck, India) with commercially available kits, blood glucose (mg/dL) and lipid profile (mg/dL) were measured.

Genotyping of CD36 rs1761667 (G/A) and CD36 rs75326924 (C/T)

The standard salting-out method was used to extract genomic DNA from venous blood leukocytes, with certain modifications[20,21]. The quantity and quality of extracted DNA were estimated using Bio-Photometer (Eppendorf, Germany) and agarose gel electrophoresis. Polymerase Chain Reaction-Restriction Fragment Length Polymorphism was used to genotype CD36 gene variants rs1761667 (G/A) and rs75326924 (C/T) using specific primers and standard polymerase chain reaction (PCR) program (Supplementary Tables 1 and 2).

Amplification, using a gradient Master Cycler (Eppendorf, Germany), involved a 15 µL reaction mixture with 100-150 ng of DNA, 200 μmol/L dNTPs, 10 pmoL of each primer, and 0.5 U of Taq DNA polymerase (GeNei, Bangalore). After amplification, the PCR products of CD36 rs1761667 (G/A) and rs75326924 (C/T) were validated on 2% agarose gel and digested with restriction enzymes HhaI and Sau96I, chosen using NEB cutter tool (ver. online) (Supplementary Tables 1 and 3).

The HhaI endonuclease breaks down the rs1761667 (G/A) product into two separate fragments of 138 bp and 52 bp, indicating the GG genotype, while the undigested 190 bp product signifies the AA genotype. Sau96I breaks the rs75326924 (C/T) product into three pieces of 243, 114, and 1 bp, corresponding to the TT genotype, whereas the undigested 358 bp product represents the CC genotype[18] (Supplementary Table 1). The PCR and digested products were separated on 2% and 3% agarose gels, stained with EtBr, and documented with a gel documentation system (Vilber Lourmat, France), Figure 1.

Figure 1 The polymerase chain reaction and digested products were separated on 2% and 3% agarose gels, stained with EtBr, and documented with a gel documentation system. A: 2% agarose gel showing CD36 gene products of 190 bp, amplified by polymerase chain reaction (PCR); B: 3% agarose gel showing PCR products digested with RE (HhaI), L1, L4, L6: GG (138 and 52 bp), L2 & L7: GA (190, 138 and 52 bp), L3 & L5: AA (190 bp) (M: 100 bp Ladder); C: 2% agarose gel showing CD36 gene products of 358 bp, amplified by PCR; D: 3% agarose gel showing PCR products digested with RE (Sau6I), L3 & L6: CC (358bp); L2, L5 & L7: CT (358, 243 and 114 bp); L1 & L4: TT (243 and 114 bp) (M: 100 bp Ladder).

Extraction of RNA and quantitative real-time polymerase chain reaction for mRNA expression analysis of CD36

RNA was extracted from venous blood leukocytes using Trizol method (Trizol reagent-Invitrogen, United States), and the quantity and quality were assessed using a biophotometer (Eppendorf, Germany). The Revert Aid First Strand kit (Thermo Scientific, United States) was utilized for cDNA synthesis. The generated cDNA was assessed for quality and quantity using a biophotometer.

The CD36 gene expression was measured by quantitative real-time polymerase chain reaction (qPCR) on a Light Cycler 480 (Roche Diagnostics, Germany). The internal control gene was GAPDH. A total reaction mixture of 10 µL was formulated using, 1X Maxima SYBR Green master mix (Thermo Scientific, United States), 25 ng cDNA, 2.5 pmol sequence-specific primers for forward and reverse reactions, and 1 µL Milli-Q water. The reaction-specific temperature was set: One cycle at 95 °C for 5 minutes, 40 cycles at 10 seconds, 57 °C for 20 seconds, 72 °C for 10 seconds, and a final hold at 10 °C for 1 minute (Supplementary Tables 4-6). Relative quantification analysis was employed for gene expression[17,20-24].

Statistical analysis

Genotypic frequencies across all groups were analyzed using a 2 × 3 contingency table, while allelic frequencies were assessed with a 2 × 2 contingency table employing the χ² test and Fisher's exact test. Continuous variables were expressed as mean ± SD within each group to assess the impact of CD36 gene polymorphisms on GDM incidence. The sample size estimation was conducted using QUANTO software (version 1.2.4). Furthermore, all reported P values were two-tailed, and differences were deemed statistically significant for P < 0.05. The computed odds ratio with 95% confidence intervals (CI) was employed to measure the magnitude of interaction[20,17,18].

RESULTS

Anthropometric and biochemical parameters of healthy pregnant and GDM women

Anthropometric and biochemical parameters of healthy pregnant women and those with GDM are demonstrated in Table 1. It was found that the GDM cases and controls were statistically significant in terms of age (P = 0.0003), gestational age (P = 0.0077), BMI (P = 0.0001), family history of diabetes (P = 0.0001), systolic blood pressure (P = 0.0066), diastolic blood pressure (P = 0.0020), fasting plasma glucose (P = 0.0001), post prandial glucose (P = 0.0001), low-density lipoprotein (LDL) (P = 0.0027), triglycerides (P = 0.0001), and. However, no statistical variations were found in the total cholesterol (P = 0.0928), high-density lipoprotein (HDL) (P = 0.0835) and serum creatinine (P = 0.828).

Table 1 Details of anthropometric parameters of controls and gestational diabetes mellitus cases, n (%).

Parameters	Controls (n = 200)	GDM (n = 200)	P value
Anthropometric parameters (mean ± SD)
Age (years)	26.74 ± 5.3	29.39 ± 5.7	0.0003a
Gestational age	24.74 ± 3.9	25.65 ± 2.5	0.0077a
Family history of diabetes
Yes	41 (19.3)	88 (43.3)	0.0001a
No	159 (80.7)	112 (56.7)
Body mass index (kg/m2)	23.97 ± 2.67	25.98 ± 2.38	0.0001a
Systolic blood pressure	124.3 ± 7.73	126.8 ± 9.98	0.0066a
Diastolic blood pressure	79.08 ± 6.44	81.39 ± 8.28	0.0020a
Biochemical parameters (mean ± SD) (mg/dL)
Fasting plasma glucose	84.2 ± 4.2	99.9 ± 4.5	0.0001a
Post prandial glucose	125.7 ± 24.57	159.9 ± 36.11	0.0001a
Total cholesterol	176.7 ± 14.3	182.2 ± 22.2	< 0.091
Triglycerides	154.7 ± 20.36	181.5 ± 30.47	0.0001a
High-density lipoprotein	51.7 ± 7.5	50.3 ± 6.9	0.0835
Low-density lipoprotein	69.53 ± 16.19	76.49 ± 22.96	0.0027a
Serum creatinine	0. 09 ± 0.7	1.1 ± 0.5	0.0828

^aP < 0.05 showed association with gestational diabetes mellitus.

Data are represented as mean ± SD. GDM: Gestational diabetes mellitus.

Genotypic analysis of CD36 rs1761667 (G/A) and CD36 rs75326924 (C/T) gene variants

The calculations of genotypic and allelic frequency distributions, as well as the determination of carriage rates of the CD36 G/A and C/T polymorphisms in 200 healthy controls and 200 GDM cases are shown in Table 2. The cases exhibited increased frequency of the 'GA' genotype of rs1761667 (G/A) and 'CT' genotype of rs75326924 (C/T) compared to the control group. The genotypes denoted as 'GA' and 'CT' of both polymorphisms exhibited a statistically significant association with an elevated risk of GDM (P = 0.0001) and (P = 0.0025), respectively. The prevalence of the 'A' allele (P = 0.001) and 'T' allele (P = 0.0019) of respective polymorphism was found to be greater in individuals with GDM as compared to those without the condition (Table 2 and Figure 1).

Table 2 Genotypic and allelic frequencies of CD36 (rs1761667) (G/A) and (rs75326924) (C/T) polymorphisms in healthy pregnant controls (n = 200) and gestational diabetes mellitus cases (n = 200).

Genotype frequency
Genotype	Control, n = 200 (%)	Case, n = 200 (%)	P value	Odd ratio 95%CI
CD36 (rs1761667)
GG	96 (44)	64 (32)	-	1.0 (Refence)
GA	58 (29)	102 (51)	0.0001	2.638 (1.695-4.190)
AA	46 (23)	34 (17)	0.7103	1.109 (0.6386-1.895)
Allelic frequency
G	250 (62.5)	230 (57.5)	0.1489	1.232 (0.9297-1.635)
A	150 (37.5)	170 (42.5)
Carriage rate
G+	154 (77)	166 (83)	0.1336	0.6857 (0.4182-1.133)
G-	46 (23)	34 (17)
A+	104 (52)	136 (68)	0.0011	0.5098 (0.3428-0.7628)
A-	96 (480	64 (32)
CD36 (rs75326924)
CC	114 (57)	82 (41)	-	1.0 (Refence)
CT	55 (27.5)	80 (40)	0.0025	2.022 (1.279-3.164)
TT	31 (15.5)	38 (19)	0.678	1.704 (0.980-2.918)
Allelic frequency
C	283 (70.75)	244 (61)	0.0046	1.546 (1.156-2.081)
T	117 (29.25)	156 (39)
Carriage rate
C+	169 (84.5)	162 (81)	0.4273	1.279 (0.754-2.129)
C-	31 (15.5)	38 (19)
T+	86 (43)	118 (59)	0.0019	0.524 (0.352-0.786)
T-	114 (57)	82 (41)

mRNA expression of CD36 gene

The mRNA expression of the CD36 gene in GDM women (case) and healthy pregnant women (control) participants was analyzed using real-time PCR (qPCR) using gene-specific primers. The mRNA expression of the CD36 gene was considerably upregulated (P = 0.001) in GDM cases compared to healthy pregnant women (Figure 2). However, the relationship between gene polymorphisms and the mRNA expression levels of the CD36 gene demonstrated no linkage (Figure 3).

Figure 2 CD36 gene expression in controls and gestational diabetes mellitus cases. GDM: Gestational diabetes mellitus.

Figure 3 Gene expression in gestational diabetes mellitus cases with different genotypes of CD36 rs1761667 (G/A) and rs75326924 (C/T) polymorphisms. A: CD36 rs1761667 (G/A); B: Rs75326924 (C/T). GDM: Gestational diabetes mellitus.

DISCUSSION

The fatty acid translocase receptor CD36 is linked to metabolic syndrome, such as, overweight and obesity, inflammation, cardiovascular disease, and thrombosis. Genetic modifications of the CD36 gene have been implicated in its altered expression, contributing to the pathophysiology of insulin resistance and several metabolic disorders[17,18,25,26]. The role of CD36 gene in the regulation of insulin homeostasis among individuals with T2DM prompted the present study to investigate the association of two SNPs (rs1761667 and rs75326924) of this gene and its expression in GDM women.

Previous studies have found that alteration in CD36 gene led to impaired myocardial fatty acid absorption associated with elevated blood lipids. An unfavorable metabolic profile was observed in diabetic individuals[17,18,27,28]. A study reported that ineffective CD36 receptor activity correlates with reduced absorption of oxidised LDLs in macrophages[29,30]. A separate investigation involving the Mexican Americans indicated that the CD36 gene is likewise correlated with HDL[31].

A case-control investigation of the Egyptian population, including patients with metabolic syndrome and healthy individuals, indicated that the CD36 gene SNP rs1761667 (G/A) has been linked with an increased risk of metabolic syndrome[25]. An additional study identified CD36 rs1761667 (G/A) as a significant predictor of kidney disease in the case of Moroccan ethnicity[32]. Similarly, the present study also found that the SNP rs1761667 (A/G) of CD36 gene has been associated with GDM in north Indian women. Alteration in the CD36 gene have led to reduced adiponectin levels and disrupted insulin regulation in individuals with T2DM and linked to susceptibility for coronary artery disease[13,33]. Another study by Enciso-Ramírez et al[34], 2021 indicated a strong association between the CD36 gene rs1761667 (G/A) with overweight and obesity in young Mexican people. Shukla et al[18], 2024 indicated that the GA genotype of CD36 rs1761667 (G/A) had the most significant association with T2DM patients in a North Indian population. Multiple CD36 gene polymorphisms were examined in T2DM cases within the North Indian population[17,18]. However, some other studies reported the AA genotype of CD36 gene polymorphism rs1761667 (G/A) is associated with reduced BMI and higher fat consumption compared to those with AG and GG genotypes in chronic hepatitis C patients[35,36].

The Heart and Aging Research in Genomic Epidemiology collaboration found 15 CD36 gene SNPs associated with stroke risk in a genome-wide association study[34]. A study on the Chinese Han population indicated that the CD36 rs3211928 gene polymorphism is correlated with ischemic stroke[37]. Another study by Lee et al[38] established a strong association between the CD36 SNP rs1761667 and stroke as well as T2DM in a Korean population, particularly among men. A study by Chu et al[39] established that the GA genotype of CD36 rs1761667 and the CT genotype of rs12998782 correlated with an elevated risk of carotid atherosclerosis in postmenopausal women of the Chinese Han population.

Numerous studies have demonstrated a significant association between SNPs in the CD36 gene and T2DM[17,18]. Insulin resistance and reduced insulin secretion are characteristic features of T2DM, which is believed to have a comparable genetic risk and pathogenesis to GDM. Consequently, it is believed that the two share a shared genetic heritage[9]. Notable differences in protein expression are implicated in the transport of free fatty acids in the placenta of humans with diabetes at term. Most of the reported alterations occur in pregnancies affected by post-gestational diabetes mellitus, characterized by elevated fetal birth weight and a high incidence of macrosomic fetuses. This indicates that disturbances in the transplacental transport of lipids may influence the enhancement of intrauterine fetal growth in women[40]. Genetic modifications are crucial as they elevate the likelihood of GDM by diminishing the ability of β-cells to mitigate the insulin resistance associated with pregnancy[41].

mRNA expression was measured in leukocytes from venous blood, which may not fully reflect expression in metabolically critical tissues like adipose tissue, placenta, or muscle. In the present study, only two SNPs in the CD36 gene (rs1761667 and rs75326924) were investigated, which may not give the effect of the full range of genetic variation in this particular gene. Additional investigation into other CD36 gene variants linked to T2DM in other studies[17,18] would facilitate the expansion of association studies regarding GDM risk susceptibility. Further research is required to determine whether other SNPs or haplotypes are associated with the likelihood of developing GDM.

CONCLUSION

GDM is a complicated disease that arises from various factors, including excessive diet and genetic dysregulation, resulting in insulin insufficiency, also known as β-cell malfunction, and insulin resistance. GDM leads to excessive hyperglycemia and hyperlipidemia, resulting in oxidative stress that produces cellular metabolic dysregulation. This influences gene expression in key pathways regulating glucose homeostasis. Genetic modifications in the CD36 gene can influence the expression of genes within these pathways increases the diabetes impact during pregnancy. The combination of genotyping research and expression investigations will be essential for advancement in GDM treatment.

ACKNOWLEDGEMENTS

The authors are grateful to the Department of Biotechnology, Indian Council of Medical Research, Department of Science and Technology, New Delhi, India, and Centre of Excellence, Higher Education, Government of Uttar Pradesh, Molecular & Human Genetics Laboratory, Department of Zoology, University of Lucknow, India.