Introduction
============

Diabetes is a type of metabolic disease characterized by hyperglycemia resulting from either defective insulin secretion, insulin action or the two ([@b1-br-0-0-921]). The most prevalent type of diabetes is type 2 diabetes mellitus (T2DM), which is one of the leading causes of morbidity globally, as well as the third-highest risk factor for premature mortality ([@b2-br-0-0-921]).

In Mexico, T2DM has led mortality rates since 2005 and today it represents the leading cause of death in the country ([@b3-br-0-0-921],[@b4-br-0-0-921]) with a prevalence of 11.8% ([@b5-br-0-0-921]). Costs associated with medical treatment of T2DM are \~450 million dollars annually ([@b6-br-0-0-921]), while \~75% of diagnosed patients do not observe adequate glycemic control even with medical assistance. These factors make T2DM a critical concern for the Mexican State\'s public health and research systems.

While genetic factors causing T2DM have not yet been sufficiently defined, they are currently under extensive study. Numerous T2DM-associated genes present as single nucleotide polymorphisms (SNPs) whose frequencies vary among different populations. Genetic variations associated with either pharmacological targets or drug metabolism are of particular interest, as different responses to pharmacological treatments may be explained by the presence of a genetic mutation or the combination of various genotypes ([@b7-br-0-0-921]).

The initial pharmacological treatments for T2DM are oral hypoglycemiants (OH), with sulfonylureas (SU) and metformin (ME) being the two most commonly administered in developing countries. SU are a type of oral OHs, which inhibit ATP-sensitive potassium channels (K~ATP~), thus inducing glucose-independent insulin release by the β-pancreatic cells ([@b8-br-0-0-921]). However, not all T2DM patients respond to the anti-diabetic action of SU (primary failure) and those who initially respond adequately may experience a decrease in its efficacy following the years (as variable as 1--2 to 10 or more years) of treatment (secondary failure) ([@b9-br-0-0-921],[@b10-br-0-0-921]). SUs are frequently combined with ME, a drug which reduces hepatic glucose production and insulin resistance ([@b11-br-0-0-921]). It has been observed that the short-term reduction of glycated hemoglobin A1c (HbA1c) is similar in SU and ME monotherapies ([@b12-br-0-0-921]), and that this drug combination reduces HbA1c more efficiently than SU alone ([@b13-br-0-0-921]). When compared, observations on the adjuvant effects of SU/ME-based treatments are inconclusive; while certain authors have associated hypoglycemic events of different severity and weight increase to SUs, either alone or in combination with ME ([@b14-br-0-0-921]), others have reported no effect on body weight when combining SUs with ME ([@b15-br-0-0-921]). However, due to their low cost and accessibility, SUs (alone or combined with ME) remain the most frequent first-line T2DM treatment in the world, particularly in developing countries, such as Mexico ([@b16-br-0-0-921],[@b17-br-0-0-921]). The UK Prospective Diabetes Study demonstrated that only 25% of patients achieved glycemic control of \<7% in HbA1c over a nine-year follow-up period of monotherapy on either SU or ME ([@b10-br-0-0-921]).

Of the genetic polymorphisms that have already been reviewed extensively and whose clinical implications have already been analyzed ([@b18-br-0-0-921],[@b19-br-0-0-921]), there are a number, which appear to be well suited for pharmacogenetic studies. Various SNPs have been reported among K~ATP~-channel encoding genes \[potassium voltage-gated channel subfamily J member 11 (*KCNJ11*) and ATP binding cassette subfamily C member 8 (*ABCC8*)\] as the therapeutic target of SU ([@b20-br-0-0-921]). Many of these genes are associated with T2DM predisposition or progression, as well as with SU response variability. A specific SNP frequency may vary between different populations; therefore, it is important to evaluate and compare its distribution among different human populations, in order to better understand whether there is an association between drug response variability, patients\' glycemic control and genetic architecture.

In the present study, the frequencies of three pharmacologically important SNPs are described in a Mestizo Mexican (MM) population and, in order to compare these with other reported populations, the distribution of *KCNJ11* rs5219 (E23K), *ABCC8* rs757110 (S1369A) and rs1799854 (−3C/T) is presented in MM T2DM patients. The aim of the present study is to increase the understanding of the genetic characteristics of specific populations. This may facilitate with elucidating the causes of therapeutic failure and the findings may also be extrapolated and/or compared to other populations in order to improve treatment options and patient management.

Materials and methods
=====================

### Patient selection and study design

This study was observational and included 247 T2DM patients recruited from July 2014 to October 2016 from two health centers: 145 from Centro de Salud Portales and 102 T2DM patients from Centro de Salud Mixcoac, both located in Mexico City\'s Benito Juárez Health Jurisdiction (Mexico). Out of the total adult patient population, 165 were females while 82 were males. Patient eligibility criteria were as follows: Self-proclaimed MM ancestry of at least three generations; age between 18 and 90 years; individuals diagnosed with T2DM according to the American Association of Diabetes criteria ([@b1-br-0-0-921]); individuals taking OHs, the SU glibenclamide alone or combined with ME, for at least 3 months. All participants were enrolled in their health centers after providing written informed consent. Patient clinical history, anthropometrics and biochemical characteristics were obtained from their clinical records (a summary of this data is presented in [Table I](#tI-br-0-0-921){ref-type="table"}).

### Genotyping

Genomic DNA was obtained by taking 6 ml peripheral blood through arm phlebotomy in glass EDTA-tubes (Vacutainer^®^; BD Biosciences, Franklin Lakes, NJ, USA) from each patient. Patients were fasted at the time of blood sampling. Genomic DNA was isolated from 200 µl total blood, using the UltraClean^®^ BloodSpin^®^ DNA Isolation kit (Mo Bio Laboratories, Inc., Carlsbad, CA, USA), and the DNA-extraction protocol was performed according to the manufacturer\'s instructions. DNA quality was achieved by electrophoresis in Invitrogen 1% agarose gels (UltraPure™ Agarose; Thermo Fisher Scientific, Inc., Waltham, MA, USA), at 100 V over 50 min. DNA concentration was measured by spectrophotometry (Jenway 7305; Cole-Parmer Ltd., Staffordshire, UK). The *KCNJ11* rs5219 (E23K), *ABCC8* rs757110 (S1369A) and rs1799854 (−3C/T) polymorphisms were determined using 20 ng total genomic DNA per reaction, by allelic discrimination via quantitative polymerase chain reaction (qPCR) using a ViiA™ 7 Real-Time PCR system and TaqMan^®^ SNP assays (Applied Biosystems; Thermo Fisher Scientific, Inc. Waltham, MA, USA) using the standard cycling conditions as follows: An initial denaturation stage 95°C for 10 min, 40 cycles of denaturation 95°C for 15 sec, and annealing at 60°C for 1 min, and post read stage or final extension at 60°C for 30 sec.

### Statistical analysis

The SNP frequencies of *KCNJ11* rs5219, ABCC8 rs757110 and rs1799854 were determined through direct counting, the remaining analyses were performed using SPSS 23.0 for Windows (IBM Corp., Armonk, NY, USA). The SNP frequencies of the patients from both health centers were compared by performing χ^2^ test of independence. In addition, biochemical and anthropometric data were compared using two-way analysis of variance (ANOVA). The total frequencies for each SNP were compared with those of other populations using the χ^2^ test of independence. P\<0.05 with 95% CI was considered to indicate a statistically significant difference.

Results
=======

### Mexican-Mestizo sample characteristics

No statistically significant differences were identified after comparing biochemical and anthropometric data from the individuals from the two health centers (data not shown). Within the whole sample, there were approximately twice as many females as there were males (162 females and 83 males); 61.5% of the patients were overweight (55.7% of females and 73.8% of males); \~25% of the subjects presented with grade I obesity (27.9% in females and 20.0% in males). The mean period since the first T2DM diagnosis was 10 years, with a mean of 7.55±0.15% for HbA1c and 141.86±4.06 mg/dl for fasting plasma glucose (FPG). A summary of anthropometrics and biochemical characteristics of our subjects is presented in [Table I](#tI-br-0-0-921){ref-type="table"}.

No significant differences were observed in genotypic and allelic frequency distribution between the two health centers (data not shown). The genotyping frequencies of the three SNPs in the whole sample were in Hardy-Weinberg equilibrium ([Table II](#tII-br-0-0-921){ref-type="table"}). The obtained allelic and genotypic frequencies were compared with those reported for other non-diabetic populations using data from the 1000 Genomes Project ([@b21-br-0-0-921]) and from literature on T2DM patients; the comparative of each SNP is presented in [Tables III](#tIII-br-0-0-921){ref-type="table"}--[V](#tV-br-0-0-921){ref-type="table"} ([@b22-br-0-0-921]--[@b38-br-0-0-921]). For the present study, studies were included that involved populations of T2DM subjects that were comparable with the current sample.

### SNP comparison with other populations

*KCNJ11* rs5219 (E23K) allelic and genotypic frequencies in MM individuals were not identified to be different between all of the T2DM populations that were compared \[predominantly European (EUR) and Asian\]. To the best of our knowledge, there were only two other studies from Mexican rs5219 allelic frequencies, which demonstrated no difference compared with the MM population: T2DM Mestizo from Yucatan and T2DM Mayans. In the 1000 Genomes Project populations, MM frequencies were only statistically different from African individuals (P=2.17E-12 and P=2.31E-19 for allelic and genotypic frequencies, respectively) and admixed American-Colombians from Medellin (P=0.002 and P=7.20E-05 for allelic and genotypic frequencies, respectively; [Table III](#tIII-br-0-0-921){ref-type="table"}).

MM *ABCC8* rs757110 (S1369A) allelic and genotypic frequencies behave similarly to rs5219. The only statistical differences were observed when compared with African individuals (P=1.45E-13 and P=1.72E-23 for allelic and genotypic frequencies, respectively) and American-Colombians from Medellin (P=6.13E-04 and P=2.52E-06 for allelic and genotypic frequencies, respectively). Currently, to the best of our knowledge, there are no other studies regarding allelic or genotypic frequencies of this SNP in a Mexican population ([Table IV](#tIV-br-0-0-921){ref-type="table"}).

*ABCC8* rs1799854 (−3C/T) SNP allelic and genotypic frequencies from MM were significantly different from all of the compared T2DM populations (primarily European and Asian). In comparison to non-diabetic populations from the 1000 Genomes Project, MM allelic and genotypic frequencies were significantly different from African individuals, East Asians, the majority of EUR individuals, and other admixed Americans from Colombia, Peru, Puerto Rico and individuals of Mexican ancestry from Los Angeles. Only in Iberic EUR and South Asian individuals did the 1000 Genomes Project report non-significant differences in allelic and genotypic frequencies compared with MM ([Table V](#tV-br-0-0-921){ref-type="table"}). Currently, to the best of our knowledge, there are no other studies on the frequencies of these SNPs among Mexican populations of non-diabetic or diabetic individuals.

Discussion
==========

In the present study, in the MM from Mexico City, rs5219 allelic and genotypic frequencies were not different from the majority of the reported populations of healthy and diabetic individuals among other ethnic groups, except for the African and Colombian subjects; the same observation applies to rs757110 ([Tables III](#tIII-br-0-0-921){ref-type="table"} and [IV](#tIV-br-0-0-921){ref-type="table"}). It appears that the distribution of these polymorphisms prevails among the majority of populations, while the ancestral allele is most frequent among African individuals. The results from the Colombian population may reflect the ancestral admixture history of the country, where the African component is widely spread across the Pacific and Caribbean regions ([@b39-br-0-0-921]--[@b41-br-0-0-921]).

In Mexican populations, rs5219 is the only SNP reported for K~ATP~-coding genes, exhibiting no differences between the alleles of healthy and T2DM subjects, even when the geographical and ethnic profile of the three Mexican samples were markedly different: The healthy volunteers were Mestizo from the South East ([@b22-br-0-0-921]), the T2DM group had Mayan Amerindian ancestry ([@b23-br-0-0-921]) and our group (MM) was formed by Mestizo individuals, primarily from the central area of Mexico.

To the best of our knowledge, this is the first report of *ABCC8* rs757110 and rs1799854 SNPs in Mexican populations, and more specifically, in diabetic Mexican patients. rs757110 allelic and genotypic frequencies behaved similarly to rs5219 SNP, which was to be expected as it is well known that these SNPs form a haplotype. Yet, rs1799854 SNP frequencies seem extremely different to those reported by the 1000 Genomes Project and the literature on various diabetic populations ([Table V](#tV-br-0-0-921){ref-type="table"}). A comparison between allelic and genotypic frequencies in the investigated group and those populations reported by the 1000 Genomes Project, demonstrated differences between all but three samples: South Asian, European and Iberic. The Iberic population may have affected the comparison result of the EUR sample, as it was included in the EUR group in the 1000 Genome Project data. This was consistent with the fact that other EUR diabetic populations from different ethnic origins were statistically different when compared with the MM group (UK, Croatia and Poland). These results may reflect the Hispanic admixture dting from Mexico\'s colonial past; however, it is interesting and unexpected that this was not observed in the other Latin-American populations reported. It was demonstrated by the results of the previous Mexican health and nutrition national survey (ENSANUT 2012) that diabetes diagnosis and first level medical attention have improved considerably in Mexico ([@b5-br-0-0-921]), yet the percentage of treated patients actually maintaining adequate glycemic control remains poor. If this lack of control is genetic, at least partially, the differences observed in Mexican genetic SNP frequencies may significantly contribute to explaining treatment failure. This first screening may facilitate with understanding where focus and investigations are required to establish whether genetic structure and pharmacological failure are associated.

It would be interesting to observe whether a healthy control group of MM individuals from central Mexico behaves the same as diabetic subjects, and to analyze groups of different ethnicity within the country to establish whether those results are consistent with or different from the present study.

The SNPs, rs5219 (E23K) and rs757110 (S1369A) form a haplotype, where K23/A1369 has been identified as a risk genotype ([@b35-br-0-0-921],[@b42-br-0-0-921],[@b43-br-0-0-921]). While electrophysiological studies have demonstrated that channels containing the K allele and K23/A1369 are less sensitive to ATP inhibition ([@b44-br-0-0-921],[@b45-br-0-0-921]), the SU response of these polymorphic channels appears to be different depending on the drug. For example, it has been shown that K23/A1369 channels are more sensitive to SU gliclazide, yet these same channels are less sensitive to inhibition by SUs, such as tolbutamide and glimepiride, while glibenclamide demonstrated no significant inhibition difference in any haplotype ([@b45-br-0-0-921],[@b46-br-0-0-921]). In another study, K allele carriers exhibited significantly higher secondary treatment failure than E allele homozygous ([@b29-br-0-0-921]) treated with SU and ME; however, Dawed *et al* ([@b19-br-0-0-921]) demonstrated that secondary failure on patients treated with a combination of SU and ME, carrying the K allele polymorphism of rs5219 may be more involved with diabetes progression than with SU response ([@b19-br-0-0-921]).

In Mexico, the most common first level treatment for T2DM combines ME with glibenclamide administration ([@b5-br-0-0-921]). In this first analysis, whose objective was mainly SNP frequency description, the authors included patients receiving glibenclamide or ME either as a mono- or combined therapy, as the SNP distribution is not affected by treatment. In future studies, the aim will be to investigate clinical implications of using ME-only treated patients as a control group to distinguish the ME effect.

The *ABCC8* rs1799854 polymorphism has been associated with a predisposition for diabetes ([@b25-br-0-0-921],[@b47-br-0-0-921],[@b48-br-0-0-921]). In terms of pharmacogenetics, certain studies have found that the TT genotype may be associated with an increase in HbA1c and triglyceride levels in SU-treated diabetics ([@b33-br-0-0-921],[@b49-br-0-0-921]), and deemed partially determinant of hyperglycemia-cardiovascular risk factor in rs1799854 heterozygotes ([@b37-br-0-0-921]). However, other authors report no significant associations when analyzing FPG and BMI ([@b28-br-0-0-921],[@b50-br-0-0-921]). Even when results in the case of this SNP are contradictory, the difference in the allelic and genotypic frequencies observed in our sample in comparison with the majority of reported cases, indicates a considerable requirement to evaluate their implications in diabetes progression and drug response in the MM population.

The SNP frequencies of rs5219 and rs757110 polymorphisms appear to be well conserved among the majority of populations, including Mexicans, there is not yet a clear association between them and the pharmacological effects. The present results may contribute to future studies to clarify whether there is a real association.

The aim of the present study was to describe the genetic architecture of three pharmacogenetically important SNPs of ABCC8 and KCNJ11 within an MM population. To the best of our knowledge, this study is the first to report allelic and genotypic frequencies of ABCC8 rs757110 and rs1799854 SNPs in an MM population. Diabetes is a major concern in Mexico, and current pharmacological treatment is considered insufficient, as shown by the latest national health survey. Therefore, understanding the characteristics of our population is a priority for elucidating a viable hypothesis to improve our knowledge of this complex pathology. It is known that interindividual responses to SU are affected by clinical factors, such as baseline glucose levels, disease duration, β-cell function and insulin resistance levels ([@b51-br-0-0-921]). However, multiple gene interaction may explain the marginal impact of each individual SNP, indicating, the necessity to construct an interaction model.

The present study was conducted as part of the Universidad Nacional Autónoma de México (National Autonomous University of Mexico-UNAM) Biological Sciences PhD postgraduate academic program fulfillment, and it was supported by the Programa de Apoyo a Proyectos de Investigación e Innovación Tecnológica (Support Program for Research and Technological Innovation Projects-PAPIIT) as the IN218216 Dirección General de Apoyo a Personal Académico (General Directorate for Academic Personnel Support-DGAPA)-UNAM project. The authors would like to thank María de los Ángeles Granados-Silvestre for her technical assistance and training in the use of the qPCR equipment and sample processing; Professor Marta Menjivar-Hiraeta for the access granted to her facility and equipment to perform qPCR experiments. To Dr Isaac González Romero (Centro de Salud Portales), Dr Mario Alberto Tinoco Centeno and Mr. José Antonio Rojas (Centro de Salud Mixcoac) for providing his technical expertise for sample collection.

MM

:   Mestizo Mexican

T2DM

:   type 2 diabetes mellitus

SNP

:   single nucleotide polymorphism

SU

:   sulfonylurea

K~ATP~

:   ATP-sensitive potassium channel

ME

:   metformin

###### 

Demographic baseline disease characteristics.

  Parameter                        Total (n=247)   Female (n=165)   Male (n=82)
  -------------------------------- --------------- ---------------- --------------
  Age (years)                      60.43±0.75      60.05 ±0.91      61.24±1.34
  Weight (kg)                      70.87±1.06      69.25±1.23       74.40±1.98
  Body mass index (kg/m^2^)        29.51±0.37      30.26±0.45       27.89±0.62
  Diabetes diagnosis (years)       10.27±0.61      9.57±0.64        11.92±1.34
  Triglycerides (mg/dl)            199.06±8.02     199.59±9.44      197.90±15.24
  Glycated hemoglobin A1c (%)      7.55±0.15       7.53±0.19        7.60±0.26
  Fasting plasma glucose (mg/dl)   141.86±4.06     144.55±5.22      135.76±5.99
  Cholesterol (mg/dl)              194.82±2.71     197.24±3.45      189.39±4.12

Values are presented as means ± standard error of the mean.

###### 

Genotypic frequencies of the analyzed polymorphisms.

  SNP       Frequency   \%      P-value
  --------- ----------- ------- ---------
  E23K                          0.69
    GG      93          37.7    
    GA      112         45.3    
    AA      42          17.0    
    Total   247         100.0   
  −3C/T                         0.55
    CC      125         50.6    
    CT      98          39.7    
    TT      24          9.7     
    Total   247         100.0   
  S1369A                        1.63
    AA      75          30.4    
    AC      131         53.0    
    CC      41          16.6    
    Total   247         100.0   

P\<3.84 using the χ^2^ test for Hardy-Weinberg equilibrium.

###### 

Potassium voltage-gated channel subfamily J member 11 rs5219 (E23K) allelic and genotypic frequency comparison.

  Author (year)                        Population          T       n      G       N      p¥                                                     TT      n     TG      n     GG      n     p¥                                                     Refs.
  ------------------------------------ ------------------- ------- ------ ------- ------ ------------------------------------------------------ ------- ----- ------- ----- ------- ----- ------------------------------------------------------ ---------------------
  1000 Genomes Project                                                                                                                                                                                                                           
  Auton *et al*                        MM                  0.603   298    0.397   196    --                                                     0.377   93    0.453   112   0.17    42                                                           ([@b21-br-0-0-921])
  \(2015\)                             AFR                 0.977   1291   0.023   31     2.17E-12^[a](#tfn3-br-0-0-921){ref-type="table-fn"}^   0.956   632   0.047   27    0.003   2     2.31E-19^[a](#tfn3-br-0-0-921){ref-type="table-fn"}^   
                                       EAS                 0.662   667    0.338   341    0.387                                                  0.429   216   0.466   235   0.105   53    0.386                                                  
                                       SAS                 0.604   591    0.396   387    0.988                                                  0.38    186   0.448   219   0.172   84    0.997                                                  
                                       EUR                 0.647   651    0.353   355    0.52                                                   0.4     201   0.495   249   0.105   53    0.406                                                  
                                       EUR IBS             0.617   132    0.383   82     0.839                                                  0.374   40    0.486   52    0.14    15    0.815                                                  
                                       AMR                 0.707   491    0.293   203    0.121                                                  0.496   172   0.424   147   0.081   28    0.084                                                  
                                       AMR CLM             0.803   151    0.197   37     0.002^[a](#tfn3-br-0-0-921){ref-type="table-fn"}^      0.638   60    0.33    31    0.032   3     7.20E-05^[a](#tfn3-br-0-0-921){ref-type="table-fn"}^   
                                       AMR MXL             0.594   76     0.406   52     0.897                                                  0.328   21    0.531   34    0.141   9     0.54                                                   
                                       AMR PEL             0.682   116    0.318   54     0.243                                                  0.435   37    0.494   42    0.071   6     0.092                                                  
                                       AMR PUR             0.712   148    0.288   60     0.104                                                  0.519   54    0.385   40    0.096   10    0.086                                                  
  Type 2 diabetic                                                                                                                                                                                                                                
  Hernandez-Escalante *et al* (2014)   AMR YCN             0.633   164    0.367   95     0.662                                                  --      --    --      --    --      --    --                                                     ([@b22-br-0-0-921])
  Lara-Riegos *et al* (2015)           AMR MYN             0.654   75     0.346   40     0.449                                                  --      --    --      --    --      --    --                                                     ([@b23-br-0-0-921])
  He *et al* (2008)                    EAS (China)         0.62    124    0.38    76     0.805                                                  0.35    35    0.54    54    0.11    11    0.34                                                   ([@b24-br-0-0-921])
  Yokoi *et al* (2006)                 EAS (Japan)         0.614   1954   0.386   1226   0.873                                                  0.384   610   0.462   734   0.155   246   0.959                                                  ([@b25-br-0-0-921])
  Holstein *et al* (2009)              EUR (Germany)       0.604   116    0.396   76     0.988                                                  0.385   37    0.437   42    0.177   17    0.975                                                  ([@b27-br-0-0-921])
  Gloyn *et al* (2001)                 EUR (UK)            0.593   427    0.407   293    0.885                                                  0.369   133   0.447   161   0.183   66    0.97                                                   ([@b28-br-0-0-921])
  Sesti *et al* (2009)                 EUR (Italy)         0.642   674    0.358   376    0.569                                                  0.385   202   0.514   270   0.101   53    0.338                                                  ([@b29-br-0-0-921])
  Ragia *et al* (2012)                 EUR (Grece)         0.668   235    0.332   117    0.339                                                  0.455   80    0.426   75    0.119   21    0.423                                                  ([@b30-br-0-0-921])
  Javorsky *et al* (2012) (Slovakia)   EUR                 0.599   121    0.401   81     0.954                                                  0.366   37    0.465   47    0.168   17    0.984                                                  ([@b31-br-0-0-921])
  Klen *et al* (2014)                  EUR (Slovenia)      0.622   194    0.378   118    0.783                                                  0.378   59    0.487   76    0.135   21    0.76                                                   ([@b32-br-0-0-921])
  Nicolac *et al* (2009)               EUR (Croatia)       0.607   277    0.393   179    0.954                                                  0.382   87    0.452   103   0.167   38    0.997                                                  ([@b33-br-0-0-921])
  Chistiakov *et al* (2009)            EUR (Russia)        0.496   128    0.504   130    0.128                                                  0.217   28    0.558   72    0.225   29    0.045^[a](#tfn3-br-0-0-921){ref-type="table-fn"}^      ([@b34-br-0-0-921])
  Sokolova *et al* (2015)              WAS (East Russia)   0.649   1926   0.351   1042   0.501                                                  0.428   635   0.442   656   0.13    193   0.647                                                  ([@b35-br-0-0-921])

P\<0.05 (95% confidence interval); p¥, c^2^ test of independence; MM, type 2 diabetic Mestizo Mexican (1000 Genomes Project third release); AFR, African individuals (1000 Genomes Project third release); EAS, East Asian individuals (1000 Genomes Project third release); SAS, East South Asian individuals (1000 Genomes Project third release); EUR, European individuals (1000 Genomes Project third release); IBS, Iberian population in Spain; AMR, Admixed American; CLM, Colombians from Medellin, Colombia; MXL, Mexican ancestry from Los Angeles, USA; PEL, Peruvians from Lima, Peru; PUR, Puerto Ricans from Puerto Rico (1000 Genomes Project third release); YCN, type 2 diabetic from Mestizo Yucatan; MYN, T2D Mayan.

###### 

ATP binding cassette subfamily C member 8 S1369A allelic and genotypic frequency comparison.

  Author (year)             Population                T       n      G       n      p¥                                                     TT      n     TG      n     GG      n     p¥                                                     Refs.
  ------------------------- ------------------------- ------- ------ ------- ------ ------------------------------------------------------ ------- ----- ------- ----- ------- ----- ------------------------------------------------------ ---------------------
  1000 Genomes Project                                                                                                                                                                                                                      
  Auton *et al*             MM                        0.569   281    0.431   213                                                           0.304   75    0.53    131   0.166   41                                                           ([@b21-br-0-0-921])
  \(2015\)                  AFR                       0.975   1289   0.025   33     1.45E-13^[a](#tfn4-br-0-0-921){ref-type="table-fn"}^   0.953   630   0.044   29    0.003   2     1.72E-23^[a](#tfn4-br-0-0-921){ref-type="table-fn"}^   
                            EAS                       0.639   644    0.361   364    0.195                                                  0.395   199   0.488   246   0.117   59    0.331                                                  
                            SAS                       0.585   572    0.415   406    0.819                                                  0.354   173   0.462   226   0.184   90    0.652                                                  
                            EUR                       0.648   652    0.352   354    0.252                                                  0.404   203   0.489   246   0.107   54    0.238                                                  
                            IBS                       0.617   132    0.383   82     0.49                                                   0.374   40    0.486   52    0.14    15    0.567                                                  
                            AMR                       0.693   481    0.307   213    0.069                                                  0.47    163   0.447   155   0.084   29    0.030^[a](#tfn4-br-0-0-921){ref-type="table-fn"}^      
                            CLM                       0.793   149    0.207   39     6.13E-04^[a](#tfn4-br-0-0-921){ref-type="table-fn"}^   0.606   57    0.372   35    0.021   2     2.52E-06^[a](#tfn4-br-0-0-921){ref-type="table-fn"}^   
                            MXL                       0.586   75     0.414   53     0.808                                                  0.328   21    0.516   33    0.156   10    0.932                                                  
                            PEL                       0.682   116    0.318   54     0.098                                                  0.435   37    0.494   42    0.071   6     0.041                                                  
                            PUR                       0.678   141    0.322   67     0.111                                                  0.462   48    0.433   45    0.106   11    0.061                                                  
  Type 2 diabetics                                                                                                                                                                                                                          
  Zhang *et al* (2007)      EAS (China)               0.565   130    0.435   100    0.954                                                  0.33    38    0.47    54    0.2     23    0.676                                                  ([@b38-br-0-0-921])
  Yokoi *et al* (2006)      EAS Japan                 0.592   1884   0.408   1296   0.742                                                  0.358   570   0.468   744   0.174   276   0.655                                                  ([@b25-br-0-0-921])
  Klen *et al* (2014)       EUR (Slovenia)            0.619   193    0.381   119    0.471                                                  0.378   59    0.481   75    0.141   22    0.536                                                  ([@b32-br-0-0-921])
  Nicolac *et al* (2009)    EUR (Croatia)             0.607   277    0.393   179    0.585                                                  0.395   90    0.425   97    0.18    41    0.301                                                  ([@b33-br-0-0-921])
  Sokolova *et al* (2015)   East Russia (West Asia)   0.623   1763   0.377   1065   0.436                                                  0.393   556   0.46    651   0.146   207   0.414                                                  ([@b35-br-0-0-921])

P\<0.05 (95% confidence interval); p¥, c^2^ test of independence; CDMX, type 2 diabetics from Mestizo Mexico City (all of the following are 1000 Genomes Project third release): AFR, African; EAS, East Asian; SAS, South Asian; EUR, European; IBS, Iberian population in Spain; AMR, Admixed American; CLM, Colombians from Medellin, Colombia; MXL, Mexican ancestry from Los Angeles, USA; PER, Peruvians from Lima, Peru; PUR, Puerto Ricans from Puerto Rico.

###### 

ATP binding cassette subfamily C member 8 −3C/T Allelic and genotypic frequency comparison.

  Authors (year)            Population      C       n      T       n      p¥                                                     CC      n     CT      n     TT      n     p¥                                                     Refs.
  ------------------------- --------------- ------- ------ ------- ------ ------------------------------------------------------ ------- ----- ------- ----- ------- ----- ------------------------------------------------------ ---------------------
  1000 Genomes Project                                                                                                                                                                                                            
  Auton *et al*             MM              0.704   348    0.296   146    --                                                     0.506   125   0.397   98    0.097   24    --                                                     ([@b21-br-0-0-921])
  \(2015\)                  AFR             0.862   1139   0.138   183    0.006^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^      0.741   490   0.241   159   0.018   12    7.96E-04^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^   
                            EAS             0.449   453    0.551   555    2.41E-04^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^   0.198   100   0.502   253   0.3     151   2.20E-06^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^   
                            SAS             0.681   666    0.319   312    0.724                                                  0.481   235   0.401   196   0.119   58    0.865                                                  
                            EUR             0.58    583    0.42    423    0.067                                                  0.33    166   0.499   251   0.171   86    0.031^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^      
                            EUR IBS         0.612   131    0.388   83     0.17                                                   0.393   42    0.439   47    0.168   18    0.169                                                  
                            AMR             0.464   322    0.536   372    5.35E-04^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^   0.225   78    0.478   166   0.297   103   1.30E-05^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^   
                            AMR CLM         0.516   97     0.484   91     0.006^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^      0.266   25    0.5     47    0.234   22    0.001^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^      
                            AMR MXL         0.422   54     0.578   74     5.10E-05^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^   0.172   11    0.5     32    0.328   21    1.35E-07^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^   
                            AMR PEL         0.312   53     0.688   117    1.91E-08^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^   0.071   6     0.482   41    0.447   38    3.15E-14^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^   
                            AMR PUR         0.567   118    0.433   90     0.044^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^      0.346   36    0.442   46    0.212   22    0.022^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^      
  Type 2 diabetics                                                                                                                                                                                                                
  He *et al* (2008)         EAS (China)     0.41    82     0.59    118    2.50E-05^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^   0.14    14    0.54    54    0.32    32    1.03E-08^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^   ([@b24-br-0-0-921])
  Yokoi *et al* (2006)      EAS (Japan)     0.474   1507   0.526   1673   8.91E-04^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^   0.233   371   0.481   765   0.286   454   2.90E-05^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^   ([@b25-br-0-0-921])
  Matharoo *et al* 2013     SAS India       0.568   227    0.433   173    0.044^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^      0.405   81    0.325   65    0.27    54    0.006^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^      ([@b36-br-0-0-921])
  Gloyn *et al* (2001)      EUR (UK)        0.464   412    0.536   476    5.35E-04^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^   0.191   85    0.545   242   0.264   117   3.50E-06^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^   ([@b28-br-0-0-921])
  Nicolac *et al* (2009)    EUR (Croatia)   0.489   223    0.511   233    0.002^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^      0.197   45    0.583   133   0.219   50    1.30E-05^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^   ([@b33-br-0-0-921])
  Dworacka *et al* (2007)   EUR (Poland)    0.45    36     0.55    44     2.54E-04^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^   0.25    10    0.4     16    0.35    14    6.00E-06^[a](#tfn5-br-0-0-921){ref-type="table-fn"}^   ([@b37-br-0-0-921])

P\<0.05 (95% confidence interval); p¥, c^2^ test of independence; CDMX, type 2 diabetics from Mestizo Mexico City (all of the following are 1000 Genomes Project third release): AFR, African; EAS, East Asian; SAS, South Asian; EUR, European; IBS, Iberian population in Spain; AMR, Admixed American; CLM, Colombians from Medellin, Colombia; MXL, Mexican ancestry from Los Angeles, USA; PER, Peruvians from Lima, Peru; PUR, Puerto Ricans from Puerto Rico.
