Analysis of Serum Circulating MicroRNAs Level in Malaysian Patients with Gestational Diabetes Mellitus

doi:10.21203/rs.3.rs-1614972/v1

Gestational diabetes mellitus is a serious global problem and needs urgent attention. Aberrant microRNAs expression is potentially disease-specific and may contribute to GDM pathological processes. Even though GDM is diagnosed at the end of the second or beginning of the third trimester, there is no way to prevent pathological changes that may occur during the first and second trimesters. Therefore, to identify a specific miRNAs expression and their predicted target genes in maternal serum subjected with GDM in especially early stage, we performed miRNA expression profiling using miRNA PCR Array and in-silico analysis. In this study, demographic data and miRNAs expression levels and their specific potential as biomarkers were investigated. The findings showed that the expression levels of hsa-miR-193a, hsa-miR-21, hsa-miR-23a, and hsa-miR-361 are significantly upregulated while miR-130a is significantly downregulated in GDM patients. The ROC curve analysis revealed that hsa-miR-193a (AUC = 0.8906 ± 0.04470, P < 0.0001), hsa-miR-21(0.8950 ± 0.04411, P < 0.0001) and miR-130a (0.7222 ± 0.07450, P = 0.0083) have a potential biomarker characteristics in GDM. Furthermore, the in-silico analysis revealed that KLF, ZNF25, AFF4, C1orf143, SRSF2, and ZNF655 were prominent genes targeted by the common nodes of miR23, miR130, miR193, miR21, and miR361. Our findings imply that circulating microRNAs in the first trimester might be used as indicators for GDM.

Biological sciences/Biochemistry

Biological sciences/Biotechnology

Biological sciences/Chemical biology

Biological sciences/Genetics

Biological sciences/Molecular biology

Health sciences/Diseases

Health sciences/Endocrinology

Health sciences/Molecular medicine

Gestational diabetes mellitus (GDM) is defined as any degree of glucose intolerance discovered during pregnancy¹. Furthermore, GDM is a risk factor for maternal and fetal morbidity during pregnancy¹. Babies born to women with GDM are more likely to have an excessive birth weight, known as macrosomia (weighing more than 4 kg), which can lead to juvenile obesity, type 2 diabetes, and/or cardiovascular disease later in life^2,3. Globally, 21.3 million pregnancies are associated with hyperglycemia, with 18.4 million pregnancies related to GDM⁴.It has been shown that GDM is a complex disease with multiple etiologies⁵. Studies have shown that the development of GDM may be the result of a combined genetic and environmental effect, but the exact cause is still unknown ⁵.GDM is diagnosed at the end of the second or early third trimester, depending on the physiological findings, and the generally accepted time for screening is the end of the second trimester, that is, between 24 and 28 weeks of pregnancy ⁶. Over the past few decades, several studies have shown that aberrant expression of miRNAs is associated with pregnancy complications and the progression of GDM⁷. miRNAs also function in blood glucose homeostasis and insulin production and secretion ⁸. Furthermore, miRNAs have been reported to be present in biological fluids such as plasma/serum of diabetic patients and are highly stable there which can be easily detected and measured⁹. MicroRNA are short, single stranded RNA that post-transcriptionally regulate gene expression¹⁰. miRNAs produced in the nucleus are pri-miRNA and they are processed into pre-miRNA that is exported to the cytoplasm by exportin-5 and converted to a mature miRNA by Dicer complex and exert their action by targeting 3′ untranslated region (3′-UTR) of mRNA resulting in inhibition of protein synthesis¹¹. Although GDM is diagnosed at the end of the second or beginning of the third trimester, using this diagnostic threshold, there is no opportunity to prevent pathological changes (accumulated damage) that may occur during first and second trimester (Undiagnosed Period). Furthermore, the implementation of screening tests such as microRNAs evaluation during early pregnancy affords opportunity to identify women at risk of disease and to evaluate intervention strategies on pregnancy outcome and the long-term health of both mother and baby³. Therefore, this study aimed to evaluate changes in the expression of circulating miRNAs in the serum of patients with GDM during the first, second and third trimesters of pregnancy and subsequent changes in miRNA expression at postpartum period.

Participant characteristics

The results demonstrated that except miscarriage, other demographics and clinical data in Table 1 were significant different (p<0.05).

MiRNA expression profiles in GDM patients

The results of the miScript miRNA PCR Array revealed a significant dysregulation pattern of miRNAs in the first, second^,third and postpartum periods (results presented in table2). In the first trimester, four miRNAs, namely hsa-miR-193a, hsa-miR-21, hsa-miR-23a, and hsa-miR-361, were significantly upregulated while only has-miR-130a was significantly downregulated in GDM patients. In the second trimester, hsa-miR-let7-i, hsa-miR-126, hsa-miR-129, were significantly upregulated and hsa-miR-125, hsa-miR-129-2, hsa-miR-130, hsa-miR-34 and hsa-miR-375 were significantly downregulated. In the third trimester, upregulation was observed with hsa-miR-let7e, hsa-miR-107, hsa-miR-361 and hsa-miR-370 while downregulated miRNAs were hsa-miR-125, hsa-miR-129 and hsa-miR-130. In the postpartum period, data analysis revealed that two microRNAs hsa-miR-194 and hsa-miR-24 are significantly upregulated and three miRNAs hsa-miR-125, hsa-miR-370, and hsa-miR-375 are significantly downregulated. A scatter plot and expression diagram of relative fold change showed the dysregulation patterns of miRNAs in a separate phase of GDM and control groups (Figure 1 and 2). Implementation of screening tests such as miRNAs evaluation during early pregnancy, offers an opportunity to identify women at risk of GDM and to evaluate intervention strategies on pregnancy outcome and the long-term health of both mother and baby. Therefore, we focused more on the results from the first trimester. Dysregulated microRNAs in the first trimester are presented in Table 3.

ROC curve analysis

The diagnostic evaluation of ROC curve based on distribution of ΔCt of dysregulated microRNAs in the 1st trimester in GDM patients revealed that the area under the curve (AUC) for hsa-miR-193a, hsa-miR-21, hsa-miR-23a, hsa-miR-361and hsa-miR-130 were 0.8906±0.04470 (P<0.0001, 95% CI=0.8-0.9), 0.8950±0.04411(P<0.0001, 95% CI=0.8-0.9),0.6337±0.08262 (P=0.1124, 95% CI=0.4-0.7) ,0.6510±0.08722(P=0.07, 95% CI=0.4-0.8) and 0.7222±0.07450 (P=0.0083, 95% CI=0.5-0.8) respectively. The data indicated that three microRNAs namely, hsa-miR-193a, hsa-miR-21and hsa-miR-130 fit the biomarker role and have a potential diagnosis value for GDM detection in the firsttrimester of pregnancy (Figure3).

In-silico target analysis

In silico analysis revealed the interaction between miRNAs and their target genes involved in the first trimester of GDM. In this analysis, KLF, ZNF25, AFF4, SRSF2, C1orf143 and ZNF655 were prominent genes targeted by the common nodes miR23, miR130, miR193, miR21, and miR361 (Figure 4).

GDM is an increasingly common condition and can cause serious and lifelong harmful complications for both mother and child. There is great interest in the potential role of miRNAs as regulators of biological processes, mediators of tissue crosstalk, and biomarkers of GDM ¹². MiRNAs participate in various mechanisms associated with pregnancy and GDM. In addition, in maternal blood, circulating miRNAs are persistent and detectable. As a result, they are potential biomarker candidates for non-invasive pregnancy problems diagnostic tests.

Studies have shown that dysregulated miRNAs are associated with pregnancy complications, suggesting the potential use as prognostic markers for GDM disease^13,14. Furthermore, previous studies have reported that serum or plasma miRNAs are differentially expressed between GDM patients and controls.

In this study, we attempted to identify the differentially expressed serum-derived miRNAs and the molecular interactions of the in-silico miRtarget genes that may be involved in GDM. Furthermore, the potential characteristics of dysregulated miRNAs were investigated. GDM is diagnosed at the end of the second or beginning of the third trimester³, leaving no time to prevent pathological changes that could occur during the first and second trimester. Thus, miRNAs detection as early as in the first trimester is crucial and was our main study objective. Our results showed that miR130a is significantly downregulated in the GDM sample, while miR193a, miR21, miR23a and miR361 were significantly upregulated in the first trimester.

MiR130a affects a variety of cellular processes, from inhibition of glucose uptake, mitochondrial function, oxidative stress to fetal development ^15,16. As a consequence of its cellular functions, miR-130a expression is deregulated in a wide range of pathologies, such as oral squamous cell carcinoma ¹⁷, ovarian epithelial cell carcinoma, thyroid eye disease ¹⁸, cervical cancer¹⁹, and acute myeloid leukemia²⁰. It was also shown that upregulated miR-130a reduces intracellular ATP levels in the pancreatic beta cell ²¹. Furthermore, previous studies found upregulation of circulating miR-130a has a crucial role in diabetes-related complications²². In a study by Meng et al., decreased miR-130a in endothelial progenitor cells from diabetes mellitus was reported to contribute to impaired EPC (Endothelial progenitor cell dysfunction) function via its target RunX3²³.

MiR23a identified from this study, has been proposed as a potential biomarker for early diagnosis of prediabetes and type 2 diabetes and is particularly useful in distinguishing between undiagnosed and prediabetes ²⁴. Our finding was in an agreement with Yang et al. in which we found that miR-23a could function as a potential biomarker in the first trimester of GDM. On the other hand, upregulated miR193a has been shown to play a vital role in the pathogenesis of placenta accreta spectrum development mediated by the target in EFNB2 gene via the EMT signaling pathway ²⁵. In addition to that, elevated miR193a was reported as a potentially new biomarker for the diagnosis of diabetic nephropathy ²⁶. Although miR193a was upregulated in the current study, and its biomarker potential was confirmed in other disease conditions, but its etiologic role in GDM is unknown and requires further study.

Literatures proven that miR21 has a significant biological route in a variety of diseases, although, as a molecular diagnostic marker can therapeutically regulate type 2 diabetes and pancreatic cancer²⁷. However, it is still unclear how miR21 is linked to GDM. One plausible explanation could be that miR21 promotes glucose uptake through induction of the PPARα gene in GDM patients and inhibits cell proliferation and infiltration²⁸. Gestational-adjusted expression of miR21 has been reported to be positively associated with GDM²⁹. Sexually dimorphic miRNA expression during pregnancy in the human placenta was reported by Amy E. Flowers et al. They found that miR361 was differentially expressed and upregulated in women of the 1st and 3rd trimesters. ³⁰. Overall, our study data investigated differentially expressed microRNAs in GDM patients and we showed the potential role of hsa-miR-193a, hsa-miR-21and hsa-miR-130a as biomarker but the role of these dysregulated microRNAs in the pathogenesis of GDM is still not clearly understood.

The findings obtained in this study showed a significant dysregulation pattern of five miRNAs hsa-miR-130a, hsa-miR-193a, hsa-miR-21, hsa-miR-23a, and hsa-miR-361 in the stage of first trimester in GDM patients. However, despite their dysregulated pattern in GDM, there are existing analytical and pre-analytical challenges that need to be addressed before the clinical use of these circulating miRNAs. The current research was conducted only on 24 GDM samples therefore, in addition, large prospective cohort studies should be performed to investigate their biological role in GDM progression and identify whether they may be diagnostic or prognostic candidates.

Participant characteristics

A case-control study was conducted on a total of 1122 women (267 GDMs and 855 controls) who had spontaneous deliveries at the University of Malaya Medical Center (UMMC) from April 2014 to June 2016. All participants were characterized by pregnancy, were nonsmokers, and did not abuse alcohol. The selection criteria for the study were the age of the mother between the ages of 18 and 45 and the diagnosis of gestational diabetes by a trained doctor. The age of mothers between the ages of 18 and 45 with normal pregnancies served as a control. Abnormal fetal, still giving birth, sickle cell anemia, thalassemia or other hemoglobinosis, and other pregnancies such as lupus, hypertension, thyroid disease, cardiovascular disease, transplantation, kidney disease, asthma or other serious disease Women diagnosed with previous conditions, drug abuse, a history of smoking and depression, and carriers of blood-borne infections were excluded. Screening was performed between the 24th and 28th weeks of gestation using the Modified Oral Glucose Tolerance Test (mOGTT). Universal screening includes pregnant women with a BMI greater than 27 kg / m2, previous giants weighing 4 kg or more, previous GDM, one-time relatives with diabetes, a history of unexpected prenatal fetal death, and birth defects. It was performed on pregnant women with a medical history Positive. GDM is defined as fasting plasma glucose (FPG) (≥5.1) and 75 g mOGTT plasma glucose (≥7.8). Substantial risk women with normal initial screening results were subjected to a repeat mOGTT at 4–6 weeks later. The control consisted of uncomplicated pregnant mothers who gave birth to a baby between 38 and 41 weeks. Trained personnel assessed the physical health of the mother and gestational age was calculated from the first day of the last menstrual cycle or from the patient's early ultrasound scan results.

Serum RNAs extraction and cDNA synthesis

Twenty-four women with GDM were included. Maternal samples were collected within first, second, third trimesters and 2-6 months postpartum. Twenty-four healthy pregnant women served as controls. Total RNAs were extracted from serum samples using the miRNeasy serum/plasma kit and synthesized into cDNA using the miScript II Rt kit according to the manufactures protocol (Qiagen, Mississauga, Ontario, Canada).

MiRNAs expression profiling

A pathway-focused miScript miRNA PCR Array Human Diabetes (Qiagen, Mississauga, Ontario, Canada) was used in combination with miScript SYBR Green PCR kit (Qiagen) to profile miRNA expression in a 96-well plate using a Step One Plus™ real time PCR detection system (Applied Biosystem, California, USA) following the cycling conditions recommended by the manufacturer’s instructions. Amplification conditions were 15 min at 95∘^C, followed by 40 cycles of 15s at 94^∘^C, 30s at 55^∘^C, and 30s at 70^∘^C. A total of 37 miRNAs involved in GDM phenotype were selected for the PCR array. Six snoRNA/snRNA, including SNORD61, SNORD68, SNORD72, SNORD95, and SNORD96A were selected as housekeeping genes. Furthermore, miRTC and PPC genes served as reverse transcription control and primer assay positive control, respectively. PCR array reactions were conducted in triplicate repeats. The data were analyzed using online Gene Globe data analysis software version 2.1.0 (https://geneglobe.qiagen.com/). The validity and accuracy of array PCR were confirmed using reverse transcription-qPCR for five randomly selected miRNAs in triplicate.

ROC curve analysis

A receiver operating characteristic (ROC) which is a plot of the true positive rate (Sensitivity) in function of the false positive rate (100-Specificity) for different cut-off points of a parameter was performed to evaluate the potential microRNAs biomarker characteristics.

Insilico Target Genes Identification and Bioinformatic Analysis

Target Scan Human Release 8.0³¹ and miRDB ³² were used to obtain predicted or previously experimentally validated miRNA target genes. Interaction network analysis was performed using the Cytoscape 3.7.1 tool to verify all potential interactions between the identified target gene and potential functional mediators.

Acknowledgements

The authors would like to thank from Pusat Perubatan Universiti Malaya (PPUM), Obstetrics & Gynaecology team for their assistance with blood collection. This research was performed using a grant support from the High Impact Research fund (University Malaya) (UM.C/625/1/HIR/ MOHE/ MED/28). This study was approved by the UMMC Medical Ethics Board (reference number 982.3), and informed consent was obtained from all participants. Also, all methods were performed in accordance with the relevant guidelines and regulations.

Author contributions

Conceptualization, SJ and SMZ.; Methodology, SJ,RV, SZM,ZM,TPC,SZO and YFP; Investigation & Statistical analysis, SJ, RV,TPC, AND HK; Writing-original Draft, SJ, and SMZ; Resources for reagents, materials and analysis tools, SJ,SZO and TPC; All authors read and approved the final manuscript.

Data availability statement

The datasets generated during and/or analysed are available from the corresponding author on reasonable request.

Competing Interests

The author(s) declare no competing interests.

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Table 1

Demographics and clinical data of the study population. Data presented as mean±SD and differences in demographical data were evaluated using ANCOVA test. P<0.05 =significant.

Characteristics	GDM (n=267)	Control (n=855)	P-Value
Age	31.31 ± 4.50	29.89 ± 4.42	0.0001
Weight	62.07 ± 12.11	55.57 ± 11.32	0.0001
BMI	26.80 ± 5.44	23.20 ± 7.92	0.0001
FPG	5.00 ± 1.48	4.26 ± 0.36	0.0001
2h FPG/ Random	9.13 ± 1.52	5.86 ± 0.93	0.0001
Previous GDM	Yes 77 (28.8%) No 190 (71.2%)	Yes 19 (2.2%) No 836 (97.8%)	0.0001
Previous C-Section	Yes 77 (28.8%) No 190 (71.2%)	Yes 99 (11.6%) No 756 (88.4%)	0.0001
Previous HBP	Yes 16 (6.0%) No 251 (94.0%)	Yes 4 (0.5%) No 851 (99.5%)	0.0001
Miscarriage	Yes 22 (8.2%) No 245 (91.8%)	Yes 55 (6.4%) No 800 (93.6%)	0.332

Table 2

Dysregulated microRNAs in each trimester and post-partum period of GDM.

Dysregulated miRNAs	Trimesters
Dysregulated miRNAs	1^st		2^nd		3^rd		Post-partum
	Fold Change	P-Value	Fold Change	P-Value	Fold Change	P-Value	Fold Change	P-Value
miR-130	-0.32	0.006	-0.43	0.004	-0.34	0.007
miR-193	3.1	0.03
miR-21	7.4	0.007
miR-23	2.14	0.01
miR-361	2.9	0.000			1.77	0.001
miR-let7i			0.71	0.008
miR-125			-0.047	0.008	-0.42	0.008	-0.21	0.01
miR-126			0.55	0.04
miR-129-2			-0.42	0.021
miR-129			0.62	0.01	-0.29	0.002
miR-34			-0.22	0.003
miR-375			-0.48	0.009			-0.31	0.021
miR-let7e					0.59	0.004
miR-107					0.57	0.002
miR-370					0.61	0.004	-0.33	0.043
miR-194							13.27	0.02
miR-24							4.85	0.04

Table 3

MiRNAs role and their putative and predictive target genes in the first trimester of GDM.

microRNAs symbol	Putative and predictive target genes /Target score98-100)	microRNA’s role in GDM	Current study
microRNAs symbol		microRNA’s role in GDM	Expression pattern/FC	P-Value
miR-130a	SRSF2, CLIP1, GJA1, CPEB1, SLAIN1, SKIDA1, ESR1, ACVR1, TSC1, RPS6KA5, MDM4, KLF, IGF1, RAP2C, ACSL4, PIK3CB, ZBTB20, MYBL1, DDX6, FAM155A, KBTBD8, ZBTB18, ZFYVE9,TBL1XR1,LGALSL, ATG16L1, RO60, CHST1, MECP2, FMR1, CNOT6, SOS2, DYNC1LI2, SECISBP2L,AMPKa,RunX3	Inhibition of glucose uptake¹⁵ Impaired mitochondrial function and oxidative stress which affects fetal development (Jiang, S et al,2017)	Decreased/-3.12	0.006548
miR-193a	SRSF2, MAPK10, PIGA, DCAF7, RAPGEF6, KLF, AFF4,EFNB2	promote trophoblast migration and invasion (Hong, Yet al.2021)	Increased/3.1	0.032241
miR-21	C1orf143, ZNF25, YOD1, PRDM11, FASLG, ZNF367, VCL, SKP2, TGFBI,PPARα	Down regulated of miR-21 Inhibit Cell Proliferation and Infiltration (Guan, C. Y et al.2020), increased miR-21 is associated with pregnancy complications (Ibarra, A et al.2018)	Increased/7.4	0.007121
miR-23a	ZNF25, ZNF99, SEMA6D, FAM234B, TRIL, INTU, ZNF138, AUH, TAB3, SEC23IP, ZBTB34, PDE7A, PPARGC1A, PDE4B, TOP1, KLF, TMED5, FUT9, SESN3, DNAJC6, PPM1K, VGLL3, SFT2D1, ZNF716, C2orf69, ATP11C, NEK6, LPP, ARHGAP20, MRC1, ETNK1, WBP2, FAM126B, TMPO, PPP4R4, HEXIM1, CCNT2, PKP4, PTEN, TNRC6A, SLC4A4, MICU3, RAB8B, CACUL1, PPIF, ZNF117, REPS2, CSNK1G3, ZFHX4, SLC1A1, MAP4K4, ROBO2, PRTG, NUFIP2, RPRD2, CTCF, SCG5, SEC24A, CDC40, BORA, CNOT6L, NCOA2, NUP50, NACC2, ZNF655	potential biomarkers for GDM in the first trimester (Yoffe, L et al.2019)	Increased/2.14	0.018739
miR-361	PIK3CG, TFAP2B, ZMAT3, RANBP17, AFF4, ZNF655, C1orf143	ultimately is a sex specific early markers of extremely low gestational age (Flowers, A. E et al.2021)	Increased/2.9	0.000063

No competing interests reported.

Analysis of Serum Circulating MicroRNAs Level in Malaysian Patients with Gestational Diabetes Mellitus

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Abstract

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Introduction

Results

Discussion

Future Directions And Conclusions

Methods

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References

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