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 Table of Contents  
ORIGINAL ARTICLE
Year : 2021  |  Volume : 9  |  Issue : 2  |  Page : 225-228

Association between phosphoglucomutase-1 gene y420h polymorphism and type 2 diabetes mellitus: A Case-control study


1 Department of Cell Biology and Molecular Genetics, Sri Devaraj Urs Academy of Higher Education and Research, Tamaka, Kolar, India
2 Department of General Medicine, Sri Devaraj Urs Medical College, Tamaka, Kolar, India
3 G2B Biologics Private Limited, National Chemical Laboratory Innovation Park, Pune, Maharashtra, India

Date of Submission30-Apr-2021
Date of Decision08-Sep-2021
Date of Acceptance09-Sep-2021
Date of Web Publication29-Dec-2021

Correspondence Address:
Dr. Sharath Balakrishna
Department of Cell Biology and Molecular Genetics, Sri Devaraj Urs Academy of Higher Education and Research, Kolar - 563 103, Karnataka
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/amhs.amhs_94_21

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  Abstract 


Background and Aim: Phosphoglucomutase 1 (PGM1) is an enzyme that catalyzes the key step that links glycogen synthesis with glucose metabolism. Single nucleotide polymorphism (SNP) (rs11208257) is a functional variant in the PGM1 gene that codes for this enzyme. Impaired glycogen synthesis is linked to type 2 diabetes mellitus (T2DM). Whether this translates into an association between SNP rs11208257 and T2DM is not known. We evaluated the association between the PGM1 gene variant (Y420H; c. 1258 T > C; rs11208257) and T2DM. Materials and Methods: We carried out a case-control study by including 225 T2DM patients and 225 age and gender-matched healthy controls. SNP rs11208257 was genotyped by a polymerase chain reaction-restriction fragment length polymorphism method. Results: Minor allele frequency was 45% in T2DM patients and 30% in healthy individuals (P = 1.4 × 10-2; Odds ratio = 1.6). The genetic model analysis showed the highest odds ratio for the additive effect of the risk allele. Conclusions: The results show that SNP rs11208257 in the PGM1 gene is associated with the risk of T2DM. This association underlines the importance of the glycogen pathway in the pathophysiology of T2DM.

Keywords: Genetic variation, glycogen pathway, phosphoglucomutase, type 2 diabetes mellitus


How to cite this article:
Praveen Kumar K S, Kamarthy P, Balakrishna S, Manu M S, Ramaswamy S. Association between phosphoglucomutase-1 gene y420h polymorphism and type 2 diabetes mellitus: A Case-control study. Arch Med Health Sci 2021;9:225-8

How to cite this URL:
Praveen Kumar K S, Kamarthy P, Balakrishna S, Manu M S, Ramaswamy S. Association between phosphoglucomutase-1 gene y420h polymorphism and type 2 diabetes mellitus: A Case-control study. Arch Med Health Sci [serial online] 2021 [cited 2022 Jul 5];9:225-8. Available from: https://www.amhsjournal.org/text.asp?2021/9/2/225/334028




  Introduction Top


Type 2 diabetes mellitus (T2DM) is a complex multifactorial disease with a genetic component. Though our understanding of the endocrinology and metabolic bases is substantial, the role of genetic factors is still nebulous. The little that is known in this direction comes mainly from rare examples of mutational defects. The role of polymorphisms, which are considerably more common than mutations, is not clear. This information is necessary for unraveling novel therapeutic targets.

Glucose is mainly utilized through the process of glycolysis. Glucose 6-phosphate (G-6-P) is the first intermediate formed after the entry of the glucose molecule into the cytoplasm. When the glucose level is higher than the cellular energy requirement, the excess glucose is converted into glycogen.[1] When the cellular glucose level is lower than the metabolic requirement, extra glucose is mobilized through the degradation of glycogen, a process known as gluconeogenesis.[2] Glycogen stores thus facilitate the balancing of glucose levels. Several lines of evidence indicate that the glycogen pathway is impaired in T2DM.[3],[4] Phosphoglucomutase 1 (PGM1) is a key enzyme that mediates the channeling of G-6-P into the glycogen pathway. PGM1 enzyme catalyzes the conversion of G-6-P into G-1-P, which is the first intermediate in the glycogen pathway [Figure 1]. Dysregulation of the PGM1 enzyme is thus likely to play an important role in the pathophysiology of T2DM.[5] Recent studies have identified a functional variant in the corresponding PGM1 gene that has been linked to a method of classification in Indian traditional medicine.[6] We hypothesized that this variant (SNP ID: Rs11208257; c. 1258 T > C; Y420H) may be associated with T2DM as it can potentially impair the glycogen pathway. The aim of the present study was to test this hypothesis.
Figure 1: Schematic representation of the role of phosphoglucomutase 1 enzyme

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  Materials and Methods Top


Study design and participants

This study was carried out by adopting a case–control design. The case group comprised patients diagnosed with T2DM. The control group comprised individuals without a history of diabetes or any other disease. The study was approved by the Institutional Ethics Committee. The samples were collected after obtaining written informed consent from the participants. The inclusion criteria for the selection of T2DM patients diagnosed with were (i) individuals of both genders (ii) between the age group 30–80 years (iii) fasting blood glucose ≥126 mg/dL (iv) HbA1c ≥6.5%.[7] The exclusion criteria for the selection were (i) microvascular complications and (ii) chronic comorbidity.

Single nucleotide polymorphism genotyping

Genomic DNA was prepared from peripheral blood samples using the salting-out method.[8] The purity and concentration of the genomic DNA preparation were determined by UV spectrophotometry (Perkin Elmer model Lambda 35, Waltham, USA). The primers were designed using the Primer Quest web-tool (Available at www.idtdna.com). Polymerase chain reaction (PCR) was set-up with the primers: 5' CCC TCC CTC AAC ATG AGA TTT G 3' and 5' CAA TTG AGA GAG GCT GGA TGA C 3'. 20 μl reaction mixture included 1X assay buffer, 100 ng genomic DNA, 0.2 mM dNTP, 10 pmol of each primer, 1.5 mM MgCl2 and 1 unit Taq polymerase (Bangalore Genei, India). The program comprised of an initial denaturation at 95³C for 3 min; 95³C for 30 s; annealing at 64³C for 30 s; 72³C for 1 min followed by 34 cycles; final extension involved 7 min at 72³C. The PCR product was analyzed by electrophoresis using 1% agarose gel. The 375 bp amplicon was subjected to restriction digestion with 5 units of NlaIII (New England Biolabs, Ipswich, USA) at 37³C for 8 h and analyzed on 2% agarose gel with ethidium bromide staining [Figure 2]. The “T” allele was visible as an uncut fragment of size 375 bp, while the C allele was cleaved to produce two fragments of sizes 226 bp and 149 bp. A Sanger sequenced sample with CC genotype was used as the positive control.
Figure 2: Representative PCR-RFLP band pattern for genotyping single nucleotide polymorphism rs11208257. Lane 1 represents TT genotype (375 bp). Lane 2 represents TC genotype (375 bp, 226 bp, and 149 bp). Lane 3 represents CC genotype (226 bp and 149 bp). Lane 4 represents undigested PCR amplicon (375 bp). Lane 5 represents 100 bp ladder

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Functional prediction of single nucleotide polymorphism

This was carried out by using the PROVEAN online software.[9] and I-Mutant 2 (http://folding.uib.es/i-mutant/imutant2.0.html). For the stability analysis of single nucleotide polymorphism (SNP), we have modeled the mutant protein and analyzed it using UCSF Chimera.

Statistical analysis

Open-Epi web-tool was used for all the statistical calculations.[10] P value from Fisher's exact test was used to determine the differences in allele and genotype distribution between the study groups. The P value was considered to be significant if it was <0.05. The conformity of the genotype frequencies in the control group with the frequencies expected from Hardy–Weinberg Equilibrium was tested using an online calculator.[11]


  Results Top


A total of 225 T2DM patients and 225 matched controls were enrolled in the study. The clinical and demographic details of the study participants are given in [Table 1]. The distribution of the alleles and the genotypes of SNP rs11208257 among T2DM and healthy controls are shown in [Table 2]. The genotype frequencies in the control group conformed with Hardy–Weinberg equilibrium (χ2 = 6.75). The minor allele “C” was very common in the control group with a frequency of 32.4%. The P value for the difference in the distribution of both genotype and allele frequencies was <0.05 [Table 2]. This indicates that the difference between the two groups was statistically significant. The frequency of the minor allele © was 1.3 times higher in the T2DM patients (44.8%) than in the healthy controls (32.4%). The distribution of the genotypes between the two groups was also analyzed by adopting various genetic models. The results are summarized in [Table 3]. The highest difference in terms of odds ratio was observed in the case of the additive genetic model.
Table 1: Clinical profile of study participants

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Table 2: Distribution of PGM1 c. 1258 T>C gene polymorphism in study participants

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Table 3: Evaluation of the association between rs11208257 SNP and type 2 diabetes mellitus under different genetic models

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The functional impact of Y420H was assessed by computational methods. The variant was found to be deleterious (PROVEAN score:-4.221). Furthermore, we used sequence and structure-based version of I-mutant 2, and the protein stability change was predicted as a decrease (-1.55 Kcal/mol) from its wild-type protein. The mutant protein model analysis indicated the loss of cation-pi interaction at the mutated site, which may drive the instability and destabilization of interaction networks with solvents.


  Discussion Top


The purpose of this study was to evaluate the association between SNP rs11208257 and T2DM. The frequency of the risk allele “C” was significantly higher in the T2DM patients than in the healthy controls. This indicates that the SNP rs11208257 is associated with the risk of developing T2DM.

A recent report, published while this manuscript was under review, identified an SNP in the intergenic region near the PGM1 gene to be associated with T2DM.[12] Whereas in this study, we have found a functional SNP within the PGM1 gene. The results of this study, therefore, independently confirm the involvement of the PGM1 gene variation in T2DM.

PGM1 enzyme plays a key role in connecting the glycogen pathway with glycolysis through the bidirectional conversion of G-6-P and G-1-P [Figure 1]. SNP rs11208257 results in a coding region substitution (p.Tyr420His) that is predicted to reduce the stability of the PGM1 enzyme. Therefore, the minor allele “C” is linked to reduced activity of the PGM1 enzyme and the consequent reduction in the interconversion of G-6-P and G-1-P. This, in turn, can compromise the glycogen pathway.[13] Since the glycogen pathway acts as a regulator of glucose metabolism, the reduced activity of the PGM1 enzyme can potentially lead to dysregulation of glucose metabolism. As dysregulated glucose metabolism is the pathophysiological hallmark of T2DM, the minor allele “C” would be expected to be relatively more common among T2DM patients than healthy controls. The pathophysiological basis for the association between SNP rs11208257 and T2DM is schematically illustrated in [Figure 3].
Figure 3: The pathophysiological basis for the association between the PGM1 gene variant single nucleotide polymorphism rs11208257 and type 2 diabetes mellitus

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The association observed in this study underlines the importance of the PGM1 enzyme in the pathophysiology of T2DM. This aspect is in concordance with the importance of the glycogen pathway in the pathophysiology of T2DM.[14] Various lines of evidence have shown that the impairment of glycogen pathway plays an important role in the pathophysiology of T2DM. Under ordinary conditions, the glycogen pathway appears to be unimportant for glucose homeostasis as the knockout of glycogen synthase does not induce any metabolic perturbations.[15] Hyperglycemia has been shown to activate the glycogen pathway in the pancreatic beta cells. Metabolic switching is assumed to protect the beta cells from the glucose-induced generation of reactive oxygen species.[16] However, excessive accumulation of glycogen also may not be appropriate for the pancreatic beta cells. Mouse pancreatic beta cells containing substantially elevated levels of glycogen show increased apoptosis than beta cells that do not contain glycogen.[17] The induction of apoptosis in the pancreatic beta cells appears to be linked to intracellular glycogen content rather than hyperglycemia. Over-expression of genes that lower glycogen content prevents apoptosis activation despite higher glucose level.[15] This evidence has led to the proposal to use the glycogen pathway as a target for developing anti-diabetic therapies.[16] The candidacy is further encouraged by the observation that metformin, the first-line anti-diabetic therapeutic, decreases the endogenous hepatic glucose level by inhibiting gluconeogenesis.[17]

The current understanding is that the dysregulation of the glycogen pathway in T2DM arises mostly due to abnormalities in the glycogen synthase enzyme. This enzyme is activated upon phosphorylation, a process regulated by two more enzymes namely glycogen synthase kinase and protein phosphatase 1. Insulin stimulates the activity of glycogen synthesis by inhibiting glycogen synthase kinase and activating protein phosphatase 1. The phosphorylation profile of glycogen synthase has been reported to be perturbed in T2DM.[18] The profile has been shown to be similar between T2DM patients and healthy controls in the preexercise period. However, the postexercise level of phosphorylation is elevated in T2DM patients. Furthermore, the elevation in the level of phosphorylation has been shown to decrease the activity of the glycogen synthase enzyme.[19]


  Conclusion Top


The results of this study show that PGM1 gene variant SNP rs11208257 is associated with the risk of T2DM. This indicates that the reduced shuttling of glucose may be one of the reasons for the impairment of the glycogen pathway in T2DM. Overall, this study underlines the role of the PGM1 gene and the glycogen pathway in the pathophysiology of T2DM. Further studies are warranted to establish the candidacy of this enzyme as an anti-diabetic drug target.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Jin GZ, Zhang Y, Cong WM, Wu X, Wang X, Wu S, et al. Phosphoglucomutase 1 inhibits hepatocellular carcinoma progression by regulating glucose trafficking. PLoS Biol 2018;16:e2006483.  Back to cited text no. 1
    
2.
Muenks AG, Stiers KM, Beamer LJ. Sequence-structure relationships, expression profiles, and disease-associated mutations in the paralogs of phosphoglucomutase 1. PLoS One 2017;12:e0183563.  Back to cited text no. 2
    
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Jensen J, Rustad PI, Kolnes AJ, Lai YC. The role of skeletal muscle glycogen breakdown for regulation of insulin sensitivity by exercise. Front Physiol 2011;2:1-11.  Back to cited text no. 3
    
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Xirouchaki CE, Mangiafico SP, Bate K, Ruan Z, Huang AM, Tedjosiswoyo BW, et al. Impaired glucose metabolism and exercise capacity with muscle-specific glycogen synthase 1 (gys1) deletion in adult mice. Mol Metab 2016;5:221-32.  Back to cited text no. 4
    
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Freymond D, Bogardus C, Okubo M, Stone K, Mott D. Impaired insulin-stimulated muscle glycogen synthase activation in vivo in man is related to low fasting glycogen synthase phosphatase activity. J Clin Invest 1988;82:1503-9.  Back to cited text no. 5
    
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Govindaraj P, Nizamuddin S, Sharath A, Jyothi V, Rotti H, Raval R, et al. Genome-wide analysis correlates Ayurveda Prakriti. Sci Rep 2015;5:15786.  Back to cited text no. 6
    
7.
Indian Council of Medical Research. Guidelines for Management of Type 2 Diabetes; 2018. Available from: http://icmr.nic.in/guidelines_diabetes/guide_diabetes.htm. [Last accessed on 2018 Jan 31].  Back to cited text no. 7
    
8.
Miller SA, Dykes DD, Polesky HF. A simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acids Res 1988;16:1215.  Back to cited text no. 8
    
9.
Choi Y, Sims GE, Murphy S, Miller JR, Chan AP. Predicting the functional effect of amino acid substitutions and indels. PLoS One 2012;7:e46688.  Back to cited text no. 9
    
10.
Dean AG, Sullivan KM, Soe MM. OpenEpi: Open Source Epidemiologic Statistics for Public Health, Version 3.0.1; 2017. Available from: https://www.OpenEpi.com. [Last accessed on 2017 Dec 01; Last updated on 2013 Apr 06].  Back to cited text no. 10
    
11.
Rodriguez S, Gaunt TR, Day IN. Hardy-Weinberg equilibrium testing of biological ascertainment for Mendelian randomization studies. Am J Epidemiol 2009;169:505-14.  Back to cited text no. 11
    
12.
Inshaw JR, Sidore C, Cucca F, Stefana MI, Crouch DJ, McCarthy MI, et al. Analysis of overlapping genetic association in type 1 and type 2 diabetes. Diabetologia 2021;64:1342-7.  Back to cited text no. 12
    
13.
Soares AF, Nissen JD, Garcia-Serrano AM, Nussbaum SS, Waagepetersen HS, Duarte JM. Glycogen metabolism is impaired in the brain of male type 2 diabetic Goto-Kakizaki rats. J Neuro Res 2019;97:1004-17.  Back to cited text no. 13
    
14.
Mir-Coll J, Duran J, Slebe F, García-Rocha M, Gomis R, Gasa R, et al. Genetic models rule out a major role of beta cell glycogen in the control of glucose homeostasis. Diabetologia 2016;59:1012-20.  Back to cited text no. 14
    
15.
Ashcroft FM, Rohm M, Clark A, Brereton MF. Is type 2 diabetes a glycogen storage disease of pancreatic β cells. Cell Metab 2017;26:17-23.  Back to cited text no. 15
    
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Pedersen AJ, Hingst JR, Friedrichsen M, Kristensen JM, Højlund K, Wojtaszewski JF. Dysregulation of muscle glycogen synthase in recovery from exercise in type 2 diabetes. Diabetologia 2015;58:1569-78.  Back to cited text no. 16
    
17.
Hundal RS, Krssak M, Dufour S, Laurent D, Lebon V, Chandramouli V, et al. Mechanism by which metformin reduces glucose production in type 2 diabetes. Diabetes 2000;49:2063-9.  Back to cited text no. 17
    
18.
Krssak M, Brehm A, Bernroider E, Anderwald C, Nowotny P, Dalla Man C, et al. Alterations in postprandial hepatic glycogen metabolism in type 2 diabetes. Diabetes 2004;53:3048-56.  Back to cited text no. 18
    
19.
Pandey MK, DeGrado TR. Glycogen synthase kinase-3 (GSK-3)-targeted therapy and imaging. Theranostics 2016;6:571-93.  Back to cited text no. 19
    


    Figures

  [Figure 1], [Figure 2], [Figure 3]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]



 

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