Literature DB >> 28607931

Genetic Epidemiology of Type 2 Diabetes in Mexican Mestizos.

Eiralí Guadalupe García-Chapa1, Evelia Leal-Ugarte1, Valeria Peralta-Leal1, Jorge Durán-González1, Juan Pablo Meza-Espinoza1.   

Abstract

There are currently about 415 million people with diabetes worldwide, a figure likely to increase to 642 million by 2040. In 2015, Mexico was the second Latin American country and sixth in the world in prevalence of this disorder with nearly 11.5 million of patients. Type 2 diabetes (T2D) is the main kind of diabetes and its etiology is complex with environmental and genetic factors involved. Indeed, polymorphisms in several genes have been associated with this disease worldwide. To estimate the genetic epidemiology of T2D in Mexican mestizos a systematic bibliographic search of published articles through PubMed, Scopus, Google Scholar, and Web of Science was conducted. Just case-control studies of candidate genes about T2D in Mexican mestizo inhabitants were included. Nineteen studies that met the inclusion criteria were found. In total, 68 polymorphisms of 41 genes were assessed; 26 of them were associated with T2D risk, which were located in ABCA1, ADRB3, CAPN10, CDC123/CAMK1D, CDKAL1, CDKN2A/2B, CRP, ELMO1, FTO, HHEX, IGF2BP2, IRS1, JAZF1, KCNQ1, LOC387761, LTA, NXPH1, SIRT1, SLC30A8, TCF7L2, and TNF-α genes. Overall, 21 of the 41 analyzed genes were associated with T2D in Mexican mestizos. Such a genetic heterogeneity compares with findings in other ethnic groups.

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Mesh:

Year:  2017        PMID: 28607931      PMCID: PMC5451767          DOI: 10.1155/2017/3937893

Source DB:  PubMed          Journal:  Biomed Res Int            Impact factor:   3.411


1. Introduction

Type 2 diabetes (T2D) is a metabolic disorder characterized by impaired glucose uptake in muscle and fat, altered glucose-induced insulin secretion, and increased hepatic glucose production, which lead to hyperglycemia. It is the most common type of diabetes and generally occurs in adults [1]. According to the International Diabetes Federation there are currently around 415 million people with diabetes worldwide, a figure likely to increase to 642 million by 2040 [2]. This disorder accounts for high morbidity and mortality due to complications like renal failure, blindness, amputations, cardiovascular disease, and cerebrovascular events [1]. In 2015 there were approximately 5.0 million deaths by diabetes worldwide [2]. With about 7.3 million patients in 2010 [3], our country was second in Latin America and tenth in the world in prevalence of this disorder [4]. Five years later, the number of diabetic patients was estimated to be 11.5 million and our country ranked sixth in the world [2]. In 2011 most frequent morbidities by T2D were renal failure (24.2%) and peripheral circulatory complications (17.3%), and the mortality rate was 70/100,000 inhabitants (http://fmdiabetes.org/wp-content/uploads/2014/11/diabetes2013INEGI.pdf). The complex etiology of T2D includes factors that influence the risk and evolution of the disease, such as ethnicity, poor alimentation, sedentary lifestyle, obesity, dyslipidemia, and family history [1, 5]. Regarding genetics, worldwide researches have shown association of this disease with numerous allelic variants of nearly 80 candidate genes [6]. The aim of this study is to carry out a literature review about genetic researches conducted in Mexican mestizos for a better understanding of the genetic epidemiology of T2D in our population.

2. Methods

A systematic search was done through PubMed, Scopus, Google Scholar, and Web of Science for genetic studies conducted in Mexican mestizo inhabitants with T2D. Key words derived from the phrase “Genetic polymorphisms associated with Diabetes Mellitus type 2 in Mexico, Mexican patients and/or Mexican mestizo” were used. Related terms such as “variants”, “alleles”, and “SNP associated with diabetes, T2DM, or T2D” complemented our search. Just case-control studies of candidate genes performed in Mexican mestizos resident in the country were included. Researches conducted in Mexican native populations were excluded, as well as those done in patients with metabolic syndrome. In surveys that included both patients with metabolic syndrome and patients with T2D, only cases with T2D were registered. Although in the selected studies different models of genotype analyses were used (recessive, dominant, or codominant), solely comparisons between allele frequencies were considered in our review. In studies without described odds ratio (OR), unadjusted OR were estimated from the reported allele or genotype frequencies. Allele comparisons were performed by 2 × 2 contingency tables [Yates' correction chi-square test (http://vassarstats.net/odds2x2.html)] and genotypes were contrasted by chi-square test (https://ihg.gsf.de/cgi-bin/hw/hwa2.pl). In both comparisons, OR were estimated using 95% confidence intervals (95% CI). A p ≤ 0.05 defined a significant association. Whenever a polymorphism was analyzed in different studies, data were combined and unadjusted OR for alleles were calculated using a 2 × 2 contingency table (Yates' correction chi-square test). However, studies with suspicion of overlapping of patients were not included in this analysis.

3. Results

In total, 19 case-control studies on the possible association of genetic polymorphisms with T2D in Mexican mestizos resident in the country were included [7-25]. Altogether, 68 polymorphisms of 41 genes were assessed (Table 1). Of them, 25 were associated with an increased risk for T2D and they were located in 20 genes, namely, ABCA1, ADRB3, CAPN10, CDC123/CAMK1D, CDKN2A/2B, CRP, ELMO1, FTO, HHEX, IGF2BP2, IRS1, JAZF1, KCNQ1, LOC387761, LTA, NXPH1, SIRT1, SLC30A8, TCF7L2, and TNF-α. Among the variants that showed association there were 4/20 amino acid substitutions, 13/30 intronic sites, 6/10 of promoter region or 5′-flanking region or upstream of gene, 1/2 intergenic regions, and 2/6 of 3′-untranslated or 3′-flanking region of gene. On the other hand, 12 polymorphisms were analyzed by different authors, and concordance was observed in most of them, except for rs3842570 (CAPN10) [11, 13, 14], rs13266634 (SLC30A4) [8, 17], rs7903146 (TCF7L2) [8, 10, 12, 22], and rs1800629 (TNF-α) [20, 24, 25]. Eleven of these polymorphisms were pooled and analyzed as shown in Table 2. Note that rs4994 (ADRB3) was discarded of this analysis (suspicion of overlap of [9, 10]). Similarly, data by Cruz et al. [10] for rs7903146 and rs12255372 of TCF7L2 were not considered (possible overlapping with the study by Martínez-Gómez et al. [12]). Thus, the 3R allele of rs3842570, which was associated with T2D in a small sample, did not seemingly confer susceptibility to the disease; in contrast, the C allele of rs7754840 (CDKAL1), which evidenced no risk in independent studies, showed association with T2D. Including this allele, a total of 26 polymorphisms and 21 genes were associated with T2D in Mexican mestizos.
Table 1

Analyzed genes in studies about type 2 diabetes conducted in Mexican mestizos.

GeneChromdbSNP locChangeEffect n a; nbOR (95% CI) p Reference
ABCA1 9q31rs9282541C/TR/C244; 202 2.50 (1.48–4.24) 0.001 [7]
rs2000069C/TIntronic244; 2021.08 (0.82–1.42)c0.58[7]
rs2230806G/AR/K244; 2021.17 (0.89–1.55)c0.27[7]
rs2487037C/TIntronic244; 2021.06 (0.79–1.43)c0.71 [7]
rs3818689G/CIntronic244; 2020.94 (0.52–1.68)c0.82 [7]

ADAMTS9 3p14rs4607103C/TIntronic1027; 9901.05 (0.91–1.20)d0.521 [8]

ADRB1 10q25rs1801253C/GR/G501; 5520.79 (0.61–1.02)c0.07 [9]

ADRB3 8p11rs4994C/TW/R519; 547 1.69 (1.37–2.09) c 0.0001 [10]
rs4994C/TW/R501; 552 1.34 (1.10–1.64) c 0.004 [9]

ARHGEF11 1q21rs945508G/AR/H868; 5040.91 (0.76–1.09)e0.319 [8]

CAPN10 2q37rs3792267G/AIntronic132; 1120.97 (0.66–1.42)c0.86 [11]
rs3792267G/AIntronic719; 7461.11 (0.95–1.29)c,f0.20 [12]
rs3792267G/AIntronic211; 1520.91 (0.66–1.26)0.56 [13]
rs38425702R/3RIntronic132; 1120.97 (0.68–1.40)c0.89 [11]
rs38425702R/3RIntronic43; 64 1.81 (1.03–3.18) c 0.038 [14]
rs38425702R/3RIntronic211; 1520.75 (0.55–1.02)0.06 [13]
rs5030952C/TIntronic132; 1130.85 (0.56–1.29)c0.45 [11]
rs5030952C/TIntronic211; 1521.35 (0.89–2.06)0.16 [13]
rs2975760T/CIntronic134; 113 2.72 (1.16–6.35) 0.017 [11]

CAPN10 2q37 rs7607759A/GT/A127; 1102.27 (0.98–5.25)c0.051 [11]

CDC123/CAMK1D 10p13rs12779790A/GIntergenic1027; 990 1.24 (1.05–1.47) d 0.013 [8]

CDKAL1 6p22rs10946398A/CIntronic519; 5471.09 (0.91–1.32)c0.337 [10]
rs9465871 C/TIntronic519; 5471.04 (0.85–1.26)c0.718 [10]
rs7754840 C/GIntronic519; 5471.08 (0.89–1.29)c0.438 [10]
rs7754840 C/GIntronic1027; 9901.13 (0.98–1.30)d,g0.081 [8]

CDKN2A/2B 9p21rs10811661C/TUpstream1027; 990 1.42 (1.15–1.75) d 0.001 [8]

CRP 1q23rs1130864C/T3′-UTR166; 130 1.59 (1.15–2.22) c,h,i 0.005 [15]
rs1205G/A3′-UTR166; 1300.82 (0.59–1.14)c,h,i0.24 [15]
rs2794521A/G5′-flanking166; 130 1.97 (1.15–3.38) c,h,i 0.012 [15]
rs3093062G/APromoter166; 130 3.49 (0.98–12.4) c,h,i 0.039 [15]

ELMO1 7p14rs1345365A/GIntronic148; 269 1.37 (1.02–1.84) c,h,i 0.035 [16]

ENPP1 6q23rs1044498A/CK/Q519; 5470.94 (0.76–1.16)c0.577 [10]

EXT2 11p11rs3740878 A/GIntronic455; 2340.83 (0.65–1.05)0.054 [17]

FTO 16q12rs8050136 A/CIntronic868; 5040.90 (0.74–1.09)e0.278 [8]
rs9939609 A/TIntronic519; 547 1.25 (1.02–1.54) c 0.027 [10]

HHEX 10q23rs5015480 C/TUpstream519; 5470.96 (0.80–1.14)c0.631 [10]
rs1111875 C/T3′-flanking1027; 9901.01 (0.89–1.16)d0.859 [8]
rs1111875 C/T3′-flanking455; 2341.12 (0.88–1.44)0.27 [17]

HHEX 10q23rs7923837A/G3′-flanking868; 504 1.21 (1.02–1.44) k 0.025 [8]

HMOX1 22q12rs2071749A/GPromoter614; 9560.98 (0.84–1.14)c0.76 [18]

IGF2BP2 3q27rs4402960G/TIntronic868; 504 1.24 (1.01–1.53) j 0.042 [8]

IRS1 2q36rs1801278G/AG/R719; 746 2.04 (1.41–2.96) c,f <0.001 [12]
rs1801278G/AG/R444; 444 3.22 (1.99–5.20) 0.001 [19]
rs1801276C/GP/A444; 4440.98 (0.72–1.32)0.83 [19]
rs3731594G/AN/D444; 4440.83 (0.42–1.66)0.47 [19]
rs1801108 G/CR/P444; 4441.07 (0.85–1.34)0.40 [19]

JAZF1 7p15rs864745 T/CIntronic868; 504 1.24 (1.04–1.47) k 0.015 [8]

KCNJ11 11p15rs5215C/TV/I519; 5471.03 (0.87–1.23)c0.729 [10]
rs5210 A/G3′-UTR519; 5471.03 (0.86–1.23)c0.764 [10]
rs5219C/TE/K1027; 9901.10 (0.96–1.26)d0.154 [8]

KCNQ1 11p15rs2237892 C/TIntronic868; 504 1.36 (1.13–1.64) k 0.001 [8]

LEPR 1p31rs1137100 A/GK/R519; 5471.00 (0.84–1.21)c0.92 [10]

LOC387761 11p12rs7480010A/GIntronic455; 234 1.43 (1.05–1.94) 0.006 [17]

LTA 6p21rs909253 A/GIntronic51; 48 1.98 (1.02–3.8) c 0.041 [20]

MGEA5 10q24MGEA5-14A/TIntronic271; 2441.60 (0.52–4.86)0.404 [21]

NOTCH2 1p11rs10923931G/TIntronic1027; 9901.04 (0.82–1.32)d0.731 [8]

NQO1 16q22rs1800566C/TP/S623; 9930.98 (0.85–1.13)c0.76 [18]

NRF2 2q31rs2364723C/GIntronic625; 9920.91 (0.79–1.05)c0.18 [18]

NRF2 2q31rs6721961C/APromoter623; 9890.89 (0.74–1.06)c0.18 [8]

NXPH1 7p22rs757705A/GIntronic868; 504 1.25 (1.05–1.48) k 0.01 [8]

PPARG 3p25rs1801282 C/GP/A719; 7461.00 (0.81–1.24)c,f1.00 [12]
rs1801282 C/GP/A1027; 9901.10 (0.90–1.34)d0.342 [8]
rs17793693 A/CIntronic519; 5471.09 (0.91–1.31)c0.329 [10]

RALGPS2 1q25rs2773080 A/GIntronic868; 5040.90 (0.74–1.10)e0.315 [8]

RORA 15q22rs7164773C/TIntronic868; 5041.08 (0.91–1.28)e0.357 [8]

SIRT1 10q21rs3758391C/TUpstream519; 547 1.29 (1.08–1.54) c 0.004 [10]

SLC30A4 8q24rs13266634 C/TR/W455; 2341.01 (0.76–1.33)0.92 [17]
rs13266634 C/TR/W1027; 990 1.22 (1.05–1.41) d 0.009 [8]

TCF7L2 10q25rs7903146C/TIntronic868; 5041.04 (0.84–1.28)e,l0.735 [8]
rs7903146C/TIntronic200; 200 1.84 (1.05–3.20) c,m 0.04 [12]
rs7903146C/TIntronic519; 547 1.48 (1.18–1.86) c 0.0007 [10]
rs7903146C/TIntronic283; 2711.25 (0.92–1.70)0.16 [22]
rs12255372G/TIntronic200; 200 1.83 (1.21–2.76) c,m 0.006 [12]
rs12255372G/TIntronic281; 268 1.78 (1.11–2.88) 0.017 [22]
rs12255372G/TIntronic519; 547 1.37 (1.06–1.76) c 0.014 [10]
DG10S478STR CACAIntronic282; 274 1.62 (1.02–2.57) 0.041 [22]

TLR2 4q32rs5743708G/A R/Q321; 5380.41 (0.04–3.7)0.40 [23]

TLR4 9q33rs4986790A/GD/G321; 5381.39 (0.42–4.56)0.58 [23]
rs4986791C/TT/I321; 5381.01 (0.32–3.18)0.98 [23]

TNF-α 6p21rs1800629-308G/AUpstream51; 480.76 (0.31–1.85)c,n0.55 [20]
rs1800629-308G/AUpstream95; 87 4.66 (1.73–12.5) c 0.001 [24]
rs1800629-308G/AUpstream259; 6451.25 (0.83–1.87)0.29 [25]
rs361525-238G/AUpstream259; 645 1.57 (1.07–2.29) 0.018 [25]

TSPAN8/LGR5 12q14–q21rs7961581C/TIntergenic868; 5040.93 (0.73–1.17)e0.516 [8]

TXNIP 1q21rs7211C/T3′ UTR623; 9690.97 (0.82–1.14)0.67 [18]

UBQLNL 11p15rs979752 C/TUpstream868; 5041.04 (0.84–1.30)e0.70 [8]

Chrom: chromosome. Risk alleles are marked in bold. na; nb. Sample for cases and controls, respectively. cConventional OR (unadjusted) was assessed by us from allele or genotype frequencies reported. dLargest n was registered. eTest without ancestry correction was considered. fCombined datasets were registered. gRisk was only observed in nonobese T2D patients (OR = 1.25; p = 0.009). hOnly Genotypes of T2D patients and healthy controls were used in our analysis. iAssessment derived from the sum of T2D patients (obese and nonobese). jThe authors reported a protector effect for the A allele (OR = 0.65; p < 0.001), but in our estimation we took as reference the A allele, since it is the most common. kSignificant analysis with ancestry correction was taken. lAssociation was only found in early-onset T2D (OR = 1.39; p = 0.024). mJust the population of Guerrero was recorded due to possible overlapping of the patients from the Mexico City with [10]. nThe G allele was assessed as risk by the authors; but in our analysis we took the A allele, the same as that in previous studies.

Table 2

Analysis of SNPs studied by two or more groups in Mexican mestizos.

GenedbSNP locCases(allele)Controls(allele) Risk allele frequency (%) OR (95% CI) p valueReference
Cases Controls
CAPN10 rs3792267108692829.528.71.06 (0.87–1.29)0.56[1113]
CAPN10 rs384257077265661.762.50.96 (0.78–1.20)0.74[11, 13, 14]
CAPN10 rs503095268653019.018.31.04 (0.78–1.40)0.78[11, 13]
CDKAL1 rs77548403092307431.429.1 1.12 (1.00–1.25) 0.044 [8, 10]
HHEX rs11118752974244862.861.71.05 (0.94–1.17)0.43[8, 17]
IRS1 rs1801278232623806.62.8 2.45 (1.83–3.28) <0.0001 [12, 19]
PPARG rs18012823492347287.386.71.05 (0.91–1.21)0.51[8, 12]
SLC30A4 rs132666342964244876.373.0 1.19 (1.05–1.35) 0.005 [8, 17]
TCF7L2 rs79031463740304217.814.1 1.32 (1.16–1.50) <0.0001 [8, 12, 22]
TCF7L2 rs122553722476258618.311.6 1.40 (1.19–1.65) <0.0001 [12, 22]
TNF-α rs1800629810156011.56.2 1.96 (1.45–2.64) <0.0001 [20, 24, 25]

Yates' correction chi-square test.

4. Discussion

This review about genetics of T2D in Mexican mestizo subjects shows that 26 polymorphisms distributed in 21 genes are associated with this disease, so T2D has a high heterogeneity in our population, the same as that in other ethnic groups. Therefore, in some individuals alleles of certain genes are involved, while in others subjects are implicated variants of different genes. A previous conclusion that T2D in Mexican mestizos is genetically homogeneous was based on an analysis of three genetic markers [26] and here appears untenable. Though the Mexican mestizo population has a European genetic ancestry near 30% [27], not all the alleles conferring diabetes risk in Europeans are associated with T2D in our population [8]. These variations could be related to genetic background, differences in clinical classifications, sample size, selection and analysis criteria, and environmental factors such as obesity, lifestyle, and diet. On the other hand, researches in several ethnic groups have shown association of T2D with genes not yet analyzed in Mexican population [5, 6, 28–32]. It would be important to carry out the analysis of such genes to determine whether these variants are also associated with T2D in Mexican patients and increase the knowledge about the genetic epidemiology of this disorder in our country. Regarding Mexican studies, an increased risk was detected when analysis was performed adjusting covariates. For instance, Cruz et al. observed an additive effect in the T2D risk when they considered variables such as age, education, sex, body mass index, and ancestry [10]. Gamboa-Meléndez et al. reported association with T2D for the polymorphisms rs7923837 (HHEX), rs4402960 (IGF2BP2), and rs2237892 (KCNQ1) only when ancestry was adjusted [8]. For the polymorphisms rs864745 (JAZF1) and rs757705 (NXPH1), the analysis stratified by ancestry did not show significant differences, whereas an association was observed in the comparison without such an adjustment. In addition, they found association for rs7903146 (TCF7L2) and rs7754840 (CDKAL1) just in early-onset T2D [OR = 1.39 (1.04–1.85), p = 0.024] and in nonobese T2D patients [OR = 1.25 (1.06–1.49), p = 0.009], respectively. Another study found a lower OR when the analysis was adjusted by sex, body mass index, and family history of T2D for three polymorphisms of IRS1 in a dominant model [19]. The reported association of rs3842570 (CAPN10) [14], rs909253 (LTA) [20], and rs1800629 (TNF-α) [24] with T2D should be interpreted with caution given the small sample sizes and poor statistical power. With respect to the rs1345365 polymorphism (ELMO1), the authors reported a protector effect for the A allele [OR = 0.65 (0.55–0.78), p < 0.001] [16]. But in our analysis we took as reference the A allele, as it is the most common; thus, the G allele showed association with T2D [OR = 1.37 (1.02 to 1.84), p = 0.035]. Since T2D is a complex disorder and several genes are implicated in its etiology and evolution, the identification of risk alleles could be useful, because if the involved genes and their function are known, it is more probable to achieve prevention, treatment, prognosis, and/or cure of the disease. Complications could also be prevented or treated better [29, 33]. However, published studies demonstrate that genetic screening for the prediction of T2D in high risk subjects is currently of little value in clinical practice. Actually, genetic risks are difficult to calculate because several alleles could contribute to an additive effect to T2D susceptibility [34], not to mention the diverse environmental factors involved. Although some of these genes are implicated in the glucose and fat metabolism, β-cell function, and sensitivity and secretion of insulin [29, 35], how some of their variants increase the T2D risk remains to be elucidated [29]. Anyway, it is fundamental to analyze the genetic epidemiology of this disease in each population because of the underlying differences in genetic background and lifestyle among ethnic groups. So, it is possible that polymorphisms associated with T2D in some races do not show association in others. Genome-wide association studies will ultimately precise the genetic landscape.
  33 in total

1.  Candidate gene association study conditioning on individual ancestry in patients with type 2 diabetes and metabolic syndrome from Mexico City.

Authors:  M Cruz; A Valladares-Salgado; J Garcia-Mena; K Ross; M Edwards; J Angeles-Martinez; C Ortega-Camarillo; J Escobedo de la Peña; A I Burguete-Garcia; N Wacher-Rodarte; R Ambriz; R Rivera; A L D'artote; J Peralta; Esteban J Parra; J Kumate
Journal:  Diabetes Metab Res Rev       Date:  2010-05       Impact factor: 4.876

2.  Admixture in Mexico City: implications for admixture mapping of type 2 diabetes genetic risk factors.

Authors:  Veronica L Martinez-Marignac; Adan Valladares; Emily Cameron; Andrea Chan; Arjuna Perera; Rachel Globus-Goldberg; Niels Wacher; Jesús Kumate; Paul McKeigue; David O'Donnell; Mark D Shriver; Miguel Cruz; Esteban J Parra
Journal:  Hum Genet       Date:  2006-10-26       Impact factor: 4.132

3.  MGEA5-14 polymorphism and type 2 diabetes in Mexico City.

Authors:  E A Cameron; V L Martinez-Marignac; A Chan; A Valladares; L V Simmonds; N Wacher; J Kumate; P McKeigue; M D Shriver; R Kittles; M Cruz; E J Parra
Journal:  Am J Hum Biol       Date:  2007 Jul-Aug       Impact factor: 1.937

4.  Association of TCF7L2 polymorphisms with type 2 diabetes in Mexico City.

Authors:  E J Parra; E Cameron; L Simmonds; A Valladares; P McKeigue; M Shriver; N Wacher; J Kumate; R Kittles; M Cruz
Journal:  Clin Genet       Date:  2007-04       Impact factor: 4.438

5.  Association of Gly972Arg polymorphism of IRS1 gene with type 2 diabetes mellitus in lean participants of a national health survey in Mexico: a candidate gene study.

Authors:  Ana I Burguete-Garcia; Miguel Cruz-Lopez; Vicente Madrid-Marina; Ruy Lopez-Ridaura; Mauricio Hernández-Avila; Bernardo Cortina; Rosa E Gómez; Eduardo Velasco-Mondragón
Journal:  Metabolism       Date:  2009-08-28       Impact factor: 8.694

6.  Association of the ATP-binding cassette transporter A1 R230C variant with early-onset type 2 diabetes in a Mexican population.

Authors:  M Teresa Villarreal-Molina; M Teresa Flores-Dorantes; Olimpia Arellano-Campos; Marisela Villalobos-Comparan; Maricela Rodríguez-Cruz; Angel Miliar-García; Adriana Huertas-Vazquez; Marta Menjivar; Sandra Romero-Hidalgo; Niels H Wacher; M Teresa Tusie-Luna; Miguel Cruz; Carlos A Aguilar-Salinas; Samuel Canizales-Quinteros
Journal:  Diabetes       Date:  2007-11-14       Impact factor: 9.461

7.  Global estimates of the prevalence of diabetes for 2010 and 2030.

Authors:  J E Shaw; R A Sicree; P Z Zimmet
Journal:  Diabetes Res Clin Pract       Date:  2009-11-06       Impact factor: 5.602

8.  Association of the calpain-10 gene with type 2 diabetes mellitus in a Mexican population.

Authors:  Laura del Bosque-Plata; Carlos A Aguilar-Salinas; María Teresa Tusié-Luna; Salvador Ramírez-Jiménez; Maribel Rodríguez-Torres; Moisés Aurón-Gómez; Erika Ramírez; María Luisa Velasco-Pérez; Alfredo Ramírez-Silva; Francisco Gómez-Pérez; Craig L Hanis; Takafumi Tsuchiya; Issei Yoshiuchi; Nancy J Cox; Graeme I Bell
Journal:  Mol Genet Metab       Date:  2004-02       Impact factor: 4.797

9.  Clinical risk factors, DNA variants, and the development of type 2 diabetes.

Authors:  Valeriya Lyssenko; Anna Jonsson; Peter Almgren; Nicoló Pulizzi; Bo Isomaa; Tiinamaija Tuomi; Göran Berglund; David Altshuler; Peter Nilsson; Leif Groop
Journal:  N Engl J Med       Date:  2008-11-20       Impact factor: 91.245

10.  Gene variants in the novel type 2 diabetes loci CDC123/CAMK1D, THADA, ADAMTS9, BCL11A, and MTNR1B affect different aspects of pancreatic beta-cell function.

Authors:  Annemarie M Simonis-Bik; Giel Nijpels; Timon W van Haeften; Jeanine J Houwing-Duistermaat; Dorret I Boomsma; Erwin Reiling; Els C van Hove; Michaela Diamant; Mark H H Kramer; Robert J Heine; J Antonie Maassen; P Eline Slagboom; Gonneke Willemsen; Jacqueline M Dekker; Elisabeth M Eekhoff; Eco J de Geus; Leen M 't Hart
Journal:  Diabetes       Date:  2009-10-15       Impact factor: 9.461

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Authors:  Leyla Karkhaneh; Ozra Tabatabaei-Malazy; Fatemeh Bandarian; Shahrzad Mohseni; Bagher Larijani
Journal:  J Diabetes Metab Disord       Date:  2021-12-01

2.  Population diversity of three variants of the SLC47A2 gene (MATE2-K transporter) in Mexican Mestizos and Native Americans.

Authors:  Alma Faviola Favela-Mendoza; Ingrid Fricke-Galindo; Wendy Fernanda Cuevas-Sánchez; José Alonso Aguilar-Velázquez; Gabriela Martínez-Cortés; Héctor Rangel-Villalobos
Journal:  Mol Biol Rep       Date:  2021-08-12       Impact factor: 2.316

3.  Antihyperglycemic and Antilipidemic Properties of a Tea Infusion of the Leaves from Annona cherimola Miller on Streptozocin-Induced Type 2 Diabetic Mice.

Authors:  Jesús Martínez-Solís; Fernando Calzada; Elizabeth Barbosa; Miguel Valdés
Journal:  Molecules       Date:  2021-04-21       Impact factor: 4.411

4.  Association of sirtuin 1 gene polymorphisms with nephrolithiasis in Eastern chinese population.

Authors:  Jiebin Hou; Jiarong Ding; Lu Li; Yonghan Peng; Xiaofeng Gao; Zhiyong Guo
Journal:  Ren Fail       Date:  2019-11       Impact factor: 2.606

5.  Association of FTO Gene Variant (rs8050136) with Type 2 Diabetes and Markers of Obesity, Glycaemic Control and Inflammation.

Authors:  Tamer Bego; Adlija Čaušević; Tanja Dujić; Maja Malenica; Zelija Velija-Asimi; Besim Prnjavorac; Janja Marc; Jana Nekvindová; Vladimír Palička; Sabina Semiz
Journal:  J Med Biochem       Date:  2019-03-03       Impact factor: 3.402

6.  In silico functional and pathway analysis of risk genes and SNPs for type 2 diabetes in Asian population.

Authors:  Md Numan Islam; Md Golam Rabby; Md Munnaf Hossen; Md Mostafa Kamal; Md Ashrafuzzaman Zahid; Md Syduzzaman; Md Mahmudul Hasan
Journal:  PLoS One       Date:  2022-08-29       Impact factor: 3.752

7.  Gene polymorphisms of Patatin-like phospholipase domain containing 3 (PNPLA3), adiponectin, leptin in diabetic obese patients.

Authors:  Omnia Aly; Hanan Hassan Zaki; Mohamed R Herzalla; Ahmed Fathy; Nermin Raafat; Mohamed M Hafez
Journal:  PLoS One       Date:  2020-06-16       Impact factor: 3.240

  7 in total

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