Skip to main content
NCBI home page
Saudi Journal of Biological Sciences logoLink to Saudi Journal of Biological Sciences
. 2014 Nov 12;22(3):243–248. doi: 10.1016/j.sjbs.2014.11.001

Screening of mitochondrial mutations and insertion–deletion polymorphism in gestational diabetes mellitus in the Asian Indian population

Imran Ali Khan a,b,c, Noor Ahmad Shaik d, Nagarjuna Pasupuleti a, Srinivas Chava b, Parveen Jahan c, Qurratulain Hasan a,b, Pragna Rao e,⁎
PMCID: PMC4423658  PMID: 25972744

Abstract

In this study we scrutinized the association between the A8344G/A3243G mutations and a 9-bp deletion polymorphism with gestational diabetes mellitus (GDM) in an Asian Indian population. The A3243G mutation in the mitochondrial tRNALeu(UUR) causes mitochondrial encephalopathy myopathy, lactic acidosis, and stroke-like episodes (MELAS), while the A8344G mutation in tRNALys causes myoclonus epilepsy with ragged red fibers (MERRF). We screened 140 pregnant women diagnosed with GDM and 140 non-GDM participants for these mutations by PCR-RFLP analysis. Both A3243G and A8344G were associated with GDM (A3243: OR-3.667, 95% CI = 1.001–13.43, p = 0.03; A8344G: OR-11.00, 95% CI = 0.6026–200.8, p = 0.04). Mitochondrial DNA mutations contribute to the development of GDM. Our results conclude that mitochondrial mutations are associated with the GDM women in our population. Thus it is important to screen other mitochondrial mutations in the GDM women.

Keywords: GDM, MELAS, A3243G, MERRF, A8344G, Mitochondria

1. Introduction

Gestational diabetes mellitus (GDM) is the most common metabolic disorder in pregnant women and is characterized by carbohydrate intolerance of variable severity with onset or first recognition during pregnancy regardless of glycemic status after delivery (Chen et al., 2000). GDM remains one of the most common clinical issues faced by obstetricians (Wang et al., 2013). The risk of developing GDM during pregnancy can be affected by genetic mutations/polymorphisms in the mother and neonates (Petry et al., 2011). GDM can produce adverse neonatal outcomes including birth defects, neonatal hypoglycemia, macrosomia, cardiac dysfunction, and long-term consequences such as increased risk for obesity, arterial hypertension, and metabolic syndrome (Lee et al., 2008). In addition, GDM has a high predictive value for later development of type 2 diabetes mellitus (T2DM) in the mother. Although insulin resistance is universally observed in pregnant women with GDM, the cellular mechanisms underlying this type of insulin resistance are not well-understood (Wang et al., 2013).

In the past decade, many efforts have been made to identify pathogenic nuclear and mitochondrial mutations in GDM. Advanced genetic approaches such as genome-wide association studies (GWAS) have identified multiple susceptibility loci in the pathogenesis of T2DM, many of which, through linkage scans, candidate gene studies, and GWAS, have also been shown to have roles in GDM, consistent with the notion that both types of diabetes share a common pathophysiology. Mutations in mitochondrial DNA (mtDNA) have been associated with a wide spectrum of clinical abnormalities, including neuromuscular disorders, heart failure, diabetes, hearing and visual loss (Brandon et al., 2005; Jacobs, 2003; Larsson, 2002; Wallace, 2005). More than 50% of these mtDNA mutations are located in 22 mitochondrial tRNA genes, including tRNALeu(UUR) (Li and Guan, 2010). mtDNA mutations have been described in association with various diseases, including T2DM (Li and Guan, 2010; Mathews and Berdanier, 1998; Duraisamy et al., 2010; Padma et al., 2010). The involvement of mtDNA in disease pathogenesis could contribute to biased maternal transmission of certain forms of diabetes.

Mitochondrial diseases are clinically heterogeneous group of disorders ranging from single-organ to severe multisystemic diseases (Chae et al., 2004). The mitochondrial tRNALeu(UUR) gene is a hotspot for pathogenic mutations associated with mitochondrial diseases with various clinical features. In fact, 21 different point mutations in this gene have been reported. Among these, the A3243G mutation has been associated with various types of mitochondrial multisystem disorders, such as mitochondrial myopathy, encephalopathy, lactic acidosis and stroke-like episodes (MELAS), maternally inherited diabetes and deafness (MIDD), myoclonus epilepsy with ragged red fibers (MERRF), maternally inherited progressive external ophthalmoplegia (PEO), hypertrophic cardiomyopathy, and Leigh syndrome (Mkaouar-Rebai et al., 2007).

Cataloged mtDNA mutations include point mutations, deletions, and duplications, the majority of which affecting transcription and translation of mtDNA are the main etiological factors of most mitochondrial diseases (Viola et al., 2008; Shen et al., 2011). One such deletion polymorphism involves the loss of one copy of a 9-bp tandem repeat (CCCCCTCTA) in the intergenic region of cytochrome c oxidase II (COII)/mitochondrial TK2 thymidine kinase 2 (MTTK) (Wrischnik et al., 1987). The “CCCCCTCTA” repeat polymorphism present between the 8271 and 8279 nucleotides of mtDNA has been well investigated in phylogenic population studies. MERRF is a multisystem mitochondrial disorder defined by myoclonus, generalized epilepsy, ataxia, and ragged-red fibers (RRFs) in muscle biopsies (Hirano, 2010). In 1992, an A to G point mutation at nucleotide position (np) 3243 in tRNALeu(UUR) was identified by a large pedigree analysis MIDD, which was later shown to be associated with diabetes in about 1.5% of the diabetic population worldwide. Subsequently, many other mutations in the tRNALeu(UUR) gene and other mtDNA regions were reported in T2DM (Crispim et al., 2008).

Maternal influence on the predisposition to GDM has also been observed, since mitochondrial transmission is exclusively maternal and both β-cell dysfunction and decreased insulin sensitivity have been associated with mtDNA mutations; thus, defective mtDNA could be a candidate gene for GDM. However, the 9-bp deletion in combination with the A3243G and A8344G mutation has also been associated with several diseases including T2DM (Crispim et al., 2008). In this study, we aimed to explore whether A8344G/A3243G mutations and the 9-bp deletion influence the occurrence of GDM in Asian Indian population.

2. Materials and methodology

2.1. Study design

We recruited 280 pregnant women from two hospitals in Hyderabad, India. Women without previous diagnosis of glucose intolerance were routinely screened for GDM between 24 and 28 weeks of gestation by a 50-g glucose challenge test (GCT). This test was considered GCT negative (GCT−) if the plasma glucose concentration was less than 7.8 mmol/L 1 h after glucose intake; otherwise, the patient was diagnosed as GCT positive (GCT+). These patients were then given a 100-g oral glucose tolerance test (OGTT). Diagnosis of GDM was based on the criteria set by the American Diabetes Association (2010). Glucose thresholds were as follows: fasting, 95 mg/dL; 1 h, 180 mg/dL; 2 h, 165 mg/dL; and 3 h, 145 mg/dL. A diagnosis of GDM was made if two or more of the values met or exceeded the threshold. Normal glucose tolerance (NGT) or non-GDM (n = 140) was diagnosed when all plasma glucose values were below the threshold values. Based on the above criteria, 140 subjects with GDM and 140 non-GDM participants were recruited. The NGT subjects were classified as normal pregnancy controls or non-GDM (Khan et al., 2014).

2.2. Clinical and biochemical data

Clinical and biochemical data for all subjects were collected between 24 and 28 weeks of gestation. Clinical data included age and weight. A family history of T2DM was also recorded. Body mass index before gestation (pre-BMI) was calculated according to Quetelet’s equation by using the weight divided by the square of height (kg/m2). Biochemical data consisted of fasting blood sugar (FBS) and postprandial blood glucose (PPBG) levels, as well as the 50-g GCT and the 100-g OGTT results.

2.3. DNA extraction

Peripheral blood (2 mL) was collected in EDTA tubes. Nucleic acids were extracted from white blood cells by salting out extraction (Khan et al., 2015). DNA quantity and quality were assessed by Nano Drop and gel electrophoresis. DNA was stored at −80 °C. The genotyping was performed at the Department of Genetics and Molecular Medicine (NABL accreditation laboratory), Kamineni Hospitals, Hyderabad, Telangana, India.

2.4. Analysis of the mitochondrial mutations

Genotyping for the A3242G and A8344G mutations was performed by polymerase chain reaction (PCR) in an Applied Biosystems thermal cycler. PCR was performed in a 50-μL volume containing 5 μL of 10× Tris buffer (cat#105878, Bangalore Genie, Bangalore, India), 4 μL of MgCl2 (25 mM; cat#METB5 Bangalore Gene, Bangalore, India), 1 μL of each dNTP (10 mM; cat# Fermentas, Hannover, MD, USA), 1 μL of each primer (10 pmol; Bioserve Biotechnology, Hyderabad, India) (Table 1), and 2.5 U Taq polymerase (cat#MME27, Bangalore Gene, Bangalore, India) as described previously (Crispim et al., 2008).

Table 1.

Mitochondrial DNA mutations detected by the PCR-RFLP method.

Gene Mutation Amino acid change Nature Primers Fragment Annealing temp Enzyme
tRNALeu(UUR) A3243G – Heteroplasmic L3029–3048/H3456–3437 501 bp 56 °C HaeIII
tRNALys A8344G – Heteroplasmic L8278–8305/H8386–8336 200 bp 60 °C AvaII
Open in a new tab

A three-step PCR for A3242G was performed as described (Khan et al., 2015). The initial denaturation at 95 °C for 5 min was followed by 35 cycles of denaturation at 95 °C for 30 s, annealing at 56 °C for 30 s for A3242G and 60 °C for 30 s for A8344G, extension at 72 °C for 45 s, and a final extension at 72 °C for 5 min. The amplified mutation products were digested with HaeIII (A3243G; cat#ER 108, MBI Fermentas, Hannover, MD, USA), and AvaII (A8344G; cat#ER 0312, MBI Fermentas, Hannover, MD, USA) in a total volume of 20 μL for 2 h at 37 °C, then separated by electrophoresis on 12% polyacrylamide gel electrophoresis. Bands were analyzed and imaged by a gel documentation system (UVI tech documentation system, Cambridge, UK).

2.5. Statistical analysis

Statistical analysis to determine the odds ratios, Yates correction, and p values was performed using Openepi for Windows, version 2.3.1 (Openepi Software, United States). The frequencies of each group in cases and controls (non-GDM) were compared with Pearson χ2/Fisher’s exact test. A p-value less than 0.05 was considered significant. The t-tests were performed with SPSS software version 19.0 (Chicago, USA).

3. Results

3.1. Characteristics of study subjects

The clinical characteristics of GDM patients and non-GDM subjects are given in Table 2. GDM cases (n = 140) had an age range of 22–38 years, 31% of them were primigravida, while 69% were multigravida. The pre-pregnancy BMI range of the GDM cases was 19.8–35.6 kg/m2 with a mean of 27.08 ± 3.93 kg/m2 and in non-GDM cases the mean was 24.10 ± 3.55 kg/m2 (p = 0.31). FBS values differ significantly between two groups i.e. cases and controls (non-GDM subjects) (p = 0.004). In the GDM group, 45% managed their diabetes with diet and exercise, while 55% of patients required 4–8 units of insulin for the remainder of the prenatal period. PPBG values were found to be significantly high in GDM cases compared with the non-GDM subjects (p < .0001).

Table 2.

Clinical characteristics of the study population.

S. No. Profiles GDM (n = 140) non-GDM (n = 140) p Value
1 Age (Years) 22–38 (29.1 ± 4.46) 17–34 (24.6 ± 3.55) 0.02
2 Weight (kg) 69.2 ± 10.43 51.2 ± 6.26 0.0001
3 BMI (kg/m2) 27.0 ± 3.93 24.1 ± 3.55 0.31
4 Mean gestational age 24.9 ± 5.01 NA NA
5 FBS (mg/dL) 121.9 ± 13.21 83.2 ± 10.37 0.004
6 PPBG (mg/dL) 158.8 ± 47.76 112.0 ± 39.70 0.0001
7 Family history 84 (60%) 56 (40%) 0.002
8 Insulin/diet (Rx) 77(55%)/63(45%) NA NA
Open in a new tab

NA = not analyzed/not applicable.

3.2. Detection of the A3243G heteroplasmic mutation

The tRNALeu(UUR) A3243G variant was assessed in all subjects. The variant was found in fourteen subjects: eleven in GDM cases and three in the non-GDM subjects. There was a significant difference in the frequency of the A3243G variants (Table 3).

Table 3.

Prevalence of mitochondrial mutations in GDM and non-GDM subjects.

Mutations GDM (n = 140) non-GDM (n = 140) p Value Odds ratio 95% CI
A3243G 7.8% (11/140) 2.1% (3/140) 0.03 3.667 (1.001–13.43)
A8344G 3.6% (5/140) 0 (0/140) 0.04⁎ 11 (0.6026–200.8)
Open in a new tab
⁎

Indicates Yates correction.

3.3. Detection of the A8344G heteroplasmic mutation

A 200-bp product of tRNALys (A8344G) was digested with AvaII to yield a 134/66 bp fragment. The frequency of the A8344G mutation in tRNALys (MERRF) was significantly high in the cases when compared with non-GDM subjects. Five variants were identified in the GDM group. Thus, there was an association between this genotype and GDM after Yates correction (Table 3).

3.4. 9-bp repeat polymorphism

The COII/MTTK gene contains a 200-bp region with a double CCCCCTCTA repeat (i.e. CCCCCTCTA–CCCCCTCTA). Insertion of a third 9-bp repeat yields a 209-bp fragment and deletion of one of the repeats yields a 191-bp fragment. In this study, the deletion polymorphism was found in 4.3% of the GDM patients; the remainder of the GDM patients carried the double repeat. None carried the insertion genotype. None of the non-GDM subjects carried an insertion or deletion genotype; thus, all carried the double repeat (Table 4).

Table 4.

Analysis of the 9-bp repeats.

Disease One repeat (deletion) Two repeats Three repeats (insertion)
GDM (n = 140) 6 (4.3%) 134 (95.7%) 0 (0.0%)
non-GDM (n = 140) 0 (0.0%) 140 (100%) 0 (0.0%)
Open in a new tab

4. Discussion

We studied 280 GDM and non-GDM pregnant women in Asian Indian subjects to characterize the association between mitochondrial mutations [tRNALeu(UUR) (A3243G) and the tRNALys gene (A8344G)/(CCCCCTCTA) polymorphism]. The clinical results showed a significant difference in age, weight, FBS, and PPBG (p < 0.05). The results recommended that there is a possible association and development of GDM in women of the Asian Indian population.

The 9-bp deletion was detected in 6% of the GDM patients. Mitochondrial mutations and GDM suggest that it may have some pathogenic roles in disease development (Chen et al., 2000). GDM is a heterogeneous group of disorders with long-term implications for the mother and fetus. Although the susceptibility to GDM is genetically determined, the role of mitochondrial mutations in the etiology of GDM is not known. Several mitochondrial mutations have been associated with human diseases such as T2DM and GDM (Chen et al., 2000; Vijaya padma et al., 2010). T2DM and GDM share a common pathophysiology that is characterized by insulin resistance and pancreatic β-cell dysfunction (Bao et al., 2012; Matharoo et al., 2013).

We found an association between the tested mutations and GDM, trembling with the previous studies we also found a similar lack of association in Singaporean women (Chen et al., 2000). To our knowledge, this is the first molecular epidemiological study of the association between A3243G, A8344G, and the 9-bp deletion and GDM in an Asian Indian women.

Repetitive and insertion/deletion DNA sequences have been found in nuclear and mtDNA and are associated with various diseases (Komandur et al., 2011). A 9-bp double CCCCCTCTA repeat in the intergenic region of MTCO2 and MTTK is polymorphic in an Asian Indian population, appearing as a single repeat (deletion) or three repeats (insertion) in <3% of the population (Thangaraj et al., 2005). The 9-bp deletion is more frequent in individuals with mt diseases such as MELAS and MERRF (Lin and Beal, 2006).

Chen et al. (2000) were unable to detect the A3243G mutation in GDM patients. The mtDNA A3243G mutation does not confer a genetic risk for GDM in Singaporean women; however, five mtDNA mutations were identified in GDM patients, including T3398C, which might have a functional role in the development of GDM. Two novel mutations (C3254A and A3399T) are also worthy of study because the sites of these mutations appear important for mitochondrial function. The A3243G mutation was not detected in this prior study, suggesting it may not majorly contribute to mild forms of diabetes such as GDM, although it could lead to the development of overt diabetes mellitus by affecting the offspring mitochondrial function (Chen et al., 2000).

A3243G mutational studies were performed in pregnant Taiwanese women (Chou et al., 2004). In this study both the mother and fetus carried the MELAS-specific A3243G mutation; however, the mtDNA level of the amniotic fluid did not significantly differ from that of the postnatal peripheral blood and hair follicles. Chou et al., 2004 concluded that MELAS syndrome may help in identifying mitochondrial mutations during pregnancy.

No studies have explored the association between the 9-bp repeat insertion–deletion polymorphism and GDM. Ours is the first report of this association. We suggest the insertion/deletion polymorphism in the untranslated region of mtDNA could have a pathogenic role in the disease, whereas A8343G and A8344G mutations have a role in GDM.

We identified six GDM women who carried the deletion genotype. Of these, five had a family history of T2DM and all five required insulin therapy. One woman was on diet and had no family history. All the women diagnosed with GDM were overweight (BMI 25–30), in their mid-30 s, and had very high fasting glucose (>100 mg/dL) and were examined at a mean gestational age of 28 weeks. Table 5 lists the demographic data of the GDM women with the deletion genotype.

Table 5.

Characteristics of the GDM cases with the single repeat variant.

S. No. Age BMI (kg/m2) FBS (mg/dL) Family history Gestational age Rx
1 30 26.2 139 Positive 28 Insulin
2 28 29.6 184 Positive 26 Insulin
3 33 29.4 128 Negative 26 Diet
4 31 27.9 121 Positive 28 Insulin
5 25 26.5 175 Positive 26 Insulin
6 29 26.3 110 Positive 32 Insulin
Open in a new tab

Duraisamy et al., 2010 performed a mitochondrial study of the A3243G variant in South Indian T2DM patients. The variant was identified in two patients with similar clinical characteristics. They concluded that these mitochondrial mutations indicate a genetic predisposition to DM in the Coimbatore South Indian population (Duraisamy et al., 2010). In our study, we found eleven mutations in the GDM cases and three in the non-GDM subjects. Earlier study by Malecki (2001) explored the A3243G variant in 129 T2DM subjects and 12 GDM cases in a Polish population. They concluded that A3243G has no role in diabetes in this population (Malecki, 2001). Another study of GDM by Allan et al. (1997) found no instances of the A3243G mutation in American women.

Lee and Wei (1997) explored the A3243G and A8344G mutations in Korean diabetics and found only one instance of A3243G in a diabetic subject. Otabe et al., 1994 reported a 0.9% frequency of A3243G in diabetic Japanese and no instances of A8344G. The A3243G mutation has been studied in various populations, none of which has shown a significant association with disease, although the mutation was identified in all tested population. A8344G was detected in our study, the results of which were consistent with all the previous studies on this subject.

5. Conclusion

Our results conclude that mitochondrial mutations are associated with the GDM women in our population. A3243G; A8344G and 9-bp repeat have a role in our study with the pregnant women. For further studies different ethnic populations are required.

Conflict of interest

None.

Acknowledgements

We are thankful to all the volunteers who have participated in this study. We are thankful to the Department of gynecology and obstetrics, Kamineni hospitals and Muslim maternity hospitals for helping with the samples. We are thankful to the Indian Council for Medical Research for the funding of this research (Sanction no. 5-3-8-39-2007; RHN).

Footnotes

Peer review under responsibility of King Saud University.

References

  1. Allan C.J., Argyropoulos G., Bowker M., Zhu J., Lin P.M., Stiver K., Golichowski A., Garvey W.T. Gestational diabetes mellitus and gene mutations which affect insulin secretion. Diab. Res. Clin. Pract. 1997;36:135–141. doi: 10.1016/s0168-8227(97)00042-9. [DOI] [PubMed] [Google Scholar]
  2. American Diabetes Association Diagnosis and classification of diabetes mellitus. Diab. Care. 2010;33:S62–S69. doi: 10.2337/dc10-S062. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Bao X.Y., Peng B., Yang M.S. Replication study of novel risk variants in six genes with type 2 diabetes and related quantitative traits in the Han Chinese lean individuals. Mol. Biol. Rep. 2012;39:2447–2454. doi: 10.1007/s11033-011-0995-8. [DOI] [PubMed] [Google Scholar]
  4. Brandon M.C., Lott M.T., Nguyen K.C., Spolim S., Navathe S.B., Baldi P. MITOMAP: a human mitochondrial genome database–2004 update. Nucleic Acids Res. 2005;33:D611–D613. doi: 10.1093/nar/gki079. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Chae J.H., Hwang H., Lim B.C., Cheong H.I., Hwang Y.S., Kim K.J. Clinical features of A3243G mitochondrial tRNA mutation. Brain Dev. 2004;26:459–462. doi: 10.1016/j.braindev.2004.01.002. [DOI] [PubMed] [Google Scholar]
  6. Chen Y., Liao W.X., Roy A.C., Loganath A., Ng S.C. Mitochondrial gene mutations in gestational diabetes mellitus. Diab. Res. Clin. Pract. 2000;48:29–35. doi: 10.1016/s0168-8227(99)00138-2. [DOI] [PubMed] [Google Scholar]
  7. Chou Y.J., Ou C.Y., Hsu T.Y., Liou C.W., Lee C.F., Tso D.J., Wei Y.H. Prenatal diagnosis of a fetus harboring an intermediate load of the A3243G mtDNA mutation in a maternal carrier diagnosed with MELAS syndrome. Prenat. Diagn. 2004;24:367–370. doi: 10.1002/pd.876. [DOI] [PubMed] [Google Scholar]
  8. Crispim D., Estivalet A.A., Roisenberg I., Gross J.L., Canani L.H. Prevalence of 15 mitochondrial DNA mutations among type 2 diabetic patients with or without clinical characteristics of maternally inherited diabetes and deafness. Arq. Bras. Endocrinol. Metab. 2008;52:1228–1235. doi: 10.1590/s0004-27302008000800005. [DOI] [PubMed] [Google Scholar]
  9. Duraisamy P., Elango S., Vishwanandha V.P., Balamurugan R. Prevalence of mitochondrial tRNA gene mutations and their association with specific clinical phenotypes in patients with type 2 diabetes mellitus of Coimbatore. Genet. Test Mol. Biomarkers. 2010;14:49–55. doi: 10.1089/gtmb.2009.0024. [DOI] [PubMed] [Google Scholar]
  10. Hirano M. A first step in viral gene therapy for muscular dystrophy. Curr. Neurol. Neurosci. Rep. 2010;10:71–72. doi: 10.1007/s11910-010-0090-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Jacobs H.T. The mitochondrial theory of aging: dead or alive? Aging Cell. 2003;2:11–17. doi: 10.1046/j.1474-9728.2003.00032.x. [DOI] [PubMed] [Google Scholar]
  12. Khan I.A., Jahan P., Hasan Q., Rao P. Angiotensin-converting enzyme gene insertion/deletion polymorphism studies in Asian Indian pregnant women biochemically identifies gestational diabetes mellitus. J. Renin Angiotensin Aldosterone Syst. 2014;15:566–571. doi: 10.1177/1470320313502106. [DOI] [PubMed] [Google Scholar]
  13. Khan I.A., Kamineni V., Poornima S., Jahan P., Hasan Q., Rao P. Tumor necrosis factor alpha promoter polymorphism studies in pregnant women. J. Reprod. Health Med. 2015;1:18–22. [Google Scholar]
  14. Komandur S., Venkatasubramanian S., Allur I.R.V., Rao P., Rao P., Hasan Q. Mitochondrial insertion–deletion polymorphism: role in disease pathology. Genet. Test Mol. Biomarkers. 2011;15:361–364. doi: 10.1089/gtmb.2010.0205. [DOI] [PubMed] [Google Scholar]
  15. Larsson N.G. Leber hereditary optic neuropathy: a nuclear solution of a mitochondrial problem. Ann. Neurol. 2002;52:529–530. doi: 10.1002/ana.10387. [DOI] [PubMed] [Google Scholar]
  16. Lee H.C., Wei Y.H. Mutation and oxidative damage of mitochondrial DNA and defective turnover of mitochondria in human aging. J. Formos. Med. Assoc. 1997;96:770–778. [PubMed] [Google Scholar]
  17. Lee H., Jang H.C., Park H.K., Metzger B.E., Cho N.H. Prevalence of type 2 diabetes among women with a previous history of gestational diabetes mellitus. Diab. Res. Clin. Pract. 2008;81:124–129. doi: 10.1016/j.diabres.2008.02.017. [DOI] [PubMed] [Google Scholar]
  18. Li R., Guan M.X. Human mitochondrial leucyl-tRNA synthetase corrects mitochondrial dysfunctions due to the tRNALeu(UUR) A3243G mutation, associated with mitochondrial encephalomyopathy, lactic acidosis, and stroke-like symptoms and diabetes. Mol. Cell. Biol. 2010;30:2147–2154. doi: 10.1128/MCB.01614-09. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Lin M.T., Beal M.F. Mitochondrial dysfunction and oxidative stress in neurodegenerative diseases. Nature. 2006;443:787–795. doi: 10.1038/nature05292. [DOI] [PubMed] [Google Scholar]
  20. Malecki M.T. Genetic basis of impaired insulin secretion, insulin resistance, the clinical picture and treatment of type 2 diabetes. Pol. Arch. Med. Wewn. 2001;105:357–363. [PubMed] [Google Scholar]
  21. Matharoo K., Arora P., Bhanwer A.J. Association of adiponectin (AdipoQ) and sulphonylurea receptor (ABCC8) gene polymorphisms with Type 2 diabetes in North Indian population of Punjab. Gene. 2013;527:228–234. doi: 10.1016/j.gene.2013.05.075. [DOI] [PubMed] [Google Scholar]
  22. Mathews C.E., Berdanier C.D. Noninsulin-dependent diabetes mellitus as a mitochondrial genomic disease. Proc. Soc. Exp. Biol. Med. 1998;219:97–108. doi: 10.3181/00379727-219-44321. [DOI] [PubMed] [Google Scholar]
  23. Mkaouar-Rebai E., Tlili A., Masmoudi S., Belguith N., Charfeddine I., Mnif M., Triki C., Fakhfakh F. Mutational analysis of the mitochondrial tRNALeu(UUR) gene in Tunisian patients with mitochondrial diseases. Biochem. Biophys. Res. Commun. 2007;355:1031–1037. doi: 10.1016/j.bbrc.2007.02.083. [DOI] [PubMed] [Google Scholar]
  24. Otabe S., Sakura H., Shimokawa K., Mori Y., Kadowaki H., Yasuda K., Nonaka K., Hagura R., Akanuma Y., Yazaki Y. The high prevalence of the diabetic patients with a mutation in the mitochondrial gene in Japan. J. Clin. Endocrinol. Metab. 1994;79:768–771. doi: 10.1210/jcem.79.3.8077358. [DOI] [PubMed] [Google Scholar]
  25. Padma V.V., Devi C.S., Kalaiselvi P. Protective effect of fish oil on changes in the activities of membrane-bound ATPases and mineral status in experimentally induced myocardial infarction in Wistar rats. Biol. Trace Elem. Res. 2010;137:344–352. doi: 10.1007/s12011-009-8590-8. [DOI] [PubMed] [Google Scholar]
  26. Petry C.J., Seear R.V., Wingate D.L., Manico L., Acerini C.L., Ong K.K., Hughes I.A., Dunger D.B. Associations between paternally transmitted fetal IGF2 variants and maternal circulating glucose concentrations in pregnancy. Diabetes. 2011;60:3090–3096. doi: 10.2337/db11-0689. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Shen L., Wei J., Chen T., He J., Qu J., He X., Jiang L., Qu Y., Fang H., Chen G., Lu J., Bai Y. Evaluating mitochondrial DNA in patients with breast cancer and benign breast disease. J. Cancer Res. Clin. Oncol. 2011;137:669–675. doi: 10.1007/s00432-010-0912-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Thangaraj K., Sridhar V., Kivisild T., Reddy A.G., Chaubey G., Singh V.K., Kaur S., Agarawal P., Rai A., Gupta J., Mallick C.B., Kumar N., Velavan T.P., Suganthan R., Udaykumar D., Kumar R., Mishra R., Khan A., Annapurna C., Singh L. Different population histories of the Mundari- and Mon-Khmer-speaking austro-asiatic tribes inferred from the mtDNA 9-bp deletion/insertion polymorphism in Indian populations. Hum. Genet. 2005;116:507–517. doi: 10.1007/s00439-005-1271-6. [DOI] [PubMed] [Google Scholar]
  29. Vijaya Padma V., Anitha S., Santhini E., Pradeepa D., Tresa D., Ganesan P., Ishwarya P., Balamurugan R. Mitochondrial and nuclear gene mutations in the type 2 diabetes patients of Coimbatore population. Mol. Cell. Biochem. 2010;345:223–229. doi: 10.1007/s11010-010-0576-5. [DOI] [PubMed] [Google Scholar]
  30. Viola G., Vedaldi D., DallAcqua F., Fortunato E., Basso G., Bianchi N., Zuccato C., Borgatti M., Lampronti I., Gambari R. Induction of gamma-globin mRNA, erythroid differentiation and apoptosis in UVA-irradiated human erythroid cells in the presence of furocoumarin derivatives. Biochem. Pharmacol. 2008;75:810–825. doi: 10.1016/j.bcp.2007.10.007. [DOI] [PubMed] [Google Scholar]
  31. Wallace D.C. Mitochondria and cancer: Warburg addressed. Cold Spring Harb. Symp. Quant. Biol. 2005;70:363–374. doi: 10.1101/sqb.2005.70.035. [DOI] [PubMed] [Google Scholar]
  32. Wang C., Li X., Huang Z., Qian J. Quantitative assessment of the influence of PPARG P12A polymorphism on gestational diabetes mellitus risk. Mol. Biol. Rep. 2013;40:811–817. doi: 10.1007/s11033-012-2119-5. [DOI] [PubMed] [Google Scholar]
  33. Wrischnik L.A., Higuchi R.G., Stoneking M., Erlich H.A., Arnheim N., Wilson A.C. Length mutations in human mitochondrial DNA: direct sequencing of enzymatically amplified DNA. Nucleic Acids Res. 1987;15:529–542. doi: 10.1093/nar/15.2.529. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Saudi Journal of Biological Sciences are provided here courtesy of Elsevier

RESOURCES