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Drug Metabolism and Personalized Therapy

Official journal of the European Society of Pharmacogenomics and Personalised Therapy

Editor-in-Chief: Llerena, Adrián

Editorial Board: Benjeddou, Mongi / Chen, Bing / Dahl, Marja-Liisa / Devinsky, Ferdinand / Hirata, Rosario / Hubacek, Jaroslav A. / Ingelman-Sundberg, Magnus / Maitland-van der Zee, Anke-Hilse / Manolopoulos, Vangelis G. / Marc, Janja / Melichar, Bohuslav / Meyer, Urs A. / Nair, Sujit / Nofziger, Charity / Peiro, Ana / Sadee, Wolfgang / Salazar, Luis A. / Simmaco, Maurizio / Turpeinen, Miia / Schaik, Ron / Shin, Jae-Gook / Visvikis-Siest, Sophie / Zanger, Ulrich M.

CiteScore 2018: 1.01

SCImago Journal Rank (SJR) 2018: 0.277
Source Normalized Impact per Paper (SNIP) 2018: 0.446

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Volume 31, Issue 2


Volume 34 (2019)

Interethnic variability of pharmacogenetic biomarkers in Mexican healthy volunteers: a report from the RIBEF (Ibero-American Network of Pharmacogenetics and Pharmacogenomics)

Ingrid Fricke-Galindo
  • Doctorate in Biological and Health Sciences, Metropolitan Autonomous University, Campus Xochimilco, Mexico City, Mexico
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Helgi Jung-Cook
  • Department of Pharmacy, Chemistry Faculty, National Autonomous University of Mexico, and Department of Neuropharmacology, National Institute of Neurology and Neurosurgery Manuel Velasco Suárez, Mexico City, Mexico
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Adrián LLerena
  • CICAB Clinical Research Centre, Extremadura University Hospital and Medical School, Badajoz, Spain
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  • De Gruyter OnlineGoogle Scholar
/ Marisol López-López
  • Corresponding author
  • Biological Systems Department, Universidad Autónoma Metropolitana, Campus Xochimilco, Calzada del Hueso 1100, Col. Villa Quietud, Coyoacán, Mexico City 04960, Mexico
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  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2016-01-14 | DOI: https://doi.org/10.1515/dmpt-2015-0030


Mexico presents a complex population diversity integrated by Mexican indigenous (MI) (7% of Mexico’s population) and Mexican mestizos (MMs). This composition highlights the importance of pharmacogenetic studies in Mexican populations. The aims of this study were to analyze the reported frequencies of the most relevant pharmacogenetic biomarkers and metabolic phenotypes in healthy volunteers from Mexican populations and to assess its interethnic variability across MI and MM populations. After a literature search in PubMed, and according to previously defined inclusion criteria, 63 pharmacogenetic studies performed in Mexican healthy volunteers up to date were selected. These reports comprised 56,292 healthy volunteers (71.58% MM). Allele frequencies in 31 pharmacogenetic biomarkers, from 121 searched, are described. Nine of these biomarkers presented variation within MM and MI groups. The frequencies of CYP2D6*3, *4, *5, *10, *17, *35 and *41 alleles in the MM group were different from those reported in the MI group. CYP2C9*2 and *3 alleles were more frequent in MM than in MI populations (χ2 test, p<0.05). CYP2C19*3 allele was not found in the MM or MI populations reported. For UGT1A1*28, only one study was found. HLA-A*31:01 and HLA-B*15:02 were present in some MM and MI populations. Poor metabolizers for CYP2D6 and CYP2C9 were more frequent in MM than in MI groups (χ2 test, p<0.05). Only 26% of the relevant pharmacogenetic biomarkers searched have been studied in Mexican healthy volunteers; therefore, further studies are warranted. The frequency variation of biomarkers in MM and MI populations could be important for the clinical implementation of pharmacogenetics in Mexico.

This article offers supplementary material which is provided at the end of the article.

Keywords: drug metabolizing enzymes; drug transporters; drug receptors; Mexicans; pharmacogenetics


It is well known that patients show interindividual variation in drug response even when they are treated with the same drug or are under the same dosage regimen. This variability is due to genetic and nongenetic factors that affect drug efficacy and safety. Age, organ function, nature of the disease and drug interactions are nongenetic factors that influence drug effects; however, there are several cases in which interindividual differences in drug response are mainly due to sequence variants in genes encoding drug-metabolizing enzymes (e.g. CYP2D6, CYP3A5, CYP2C9, CYP2C19, NAT2, TPMT, UGT1A1 and UGT1A4), drug transporters (e.g. ABCB1, ABCC2, OATP1B1 and SLCO2B1), or drug receptors (e.g. ADRB2, EGFR, DRD2, ERBB2 and RYR1) [14]. Regulatory agencies, such as the Food and Drug Administration (FDA) and the European Medicines Agency (EMA), have established a wide variety of genetic polymorphisms as biomarkers for therapeutic recommendations or safety warnings [57]. However, in Latin American countries, this information has not been widely considered in regulatory agencies. For instance, in Mexico, the Federal Commission for Protection against Health Risks (COFEPRIS) has not yet included pharmacogenetic considerations for therapeutic or safety recommendations.

Moreover, variations on drug-metabolizing enzymes and transporters not only affect drug response or toxicity but also impact the metabolism of endogenous substrates, and they have been related with neurological disorders as depression and suicide [810].

The use of pharmacogenetic biomarkers in clinical practice should consider ethnic, cultural and socioeconomical variations, as well as the genetic heterogeneity among regions and nations [7, 11]. For example, several studies have shown the interethnic variability of biomarkers’ frequencies as in the case of CYP2D6 [12], CYP2C9 and CYP2C19 [13], UGT1A1 [14] and HLA [1518], whereas other investigations have reported the importance to perform pharmacogenetic studies in different ethnic groups [1921].

Ibero-American populations present a genetic heterogeneity and complex population diversity because of differences in human development index, colonial histories and population structure [11]. Therefore, the study of biomarkers on these distinctive populations is relevant to the development of pharmacogenetics and personalized medicine [22].

Mexico is the 11th most populated country worldwide, with more than 112 million of inhabitants [23]. Geographically distant regions in Mexico have different population dynamics related to both ancestral components diversity and demographic conditions of each region [24]. Moreover, this country harbors one of the largest sources of pre-Columbian diversity and has a history of complex civilizations with different contributions to the current population [25].

Mexican indigenous (MI) account for at least 60 different native groups, representing 7% of Mexico’s current population [26]. This population, as well as other American indigenous populations and individuals with indigenous ancestry, could carry local private alleles rare or absent elsewhere, including functional and medically relevant variants, because of the lowest genetic diversity characteristic of these groups [27, 28].

Mexican mestizos (MMs) have resulted because of the admixture of Amerindian indigenous groups for the past 500 years with European and, to a lesser extent, African populations [29]. MMs are known to be genetically different among the 30 Mexican states, with an Amerindian admixture ranging from 30% to 70% [26]. This unique demographic history highlights the importance to consider the genetic background of the populations in pharmacogenetic studies in Mexico [24].

Although two previous reports have reviewed the pharmacogenetic studies conducted in Mexican populations [30, 31], they have only considered some drug-metabolizing enzymes. Nevertheless, it is also important to describe the investigations of other biomarkers as drug transporters and receptors. Therefore, the aims of this study were to analyze the reported frequencies of the most relevant pharmacogenetic biomarkers and metabolic phenotypes in healthy volunteers from Mexican populations and to assess its interethnic variability across MI and MM populations. The present investigation is coordinated by RIBEF (Red Ibero-Latino Americana de Farmacogenética y Farmacogenómica, http://www.ribef.com), which addresses the study of pharmacogenetic data available in Latin American populations. RIBEF is a collaboration network that brings together more than 40 research groups with the aim to increase the pharmacogenetic knowledge in this multiethnic and multicultural region.


We performed a literature search in PubMed database on June 2015, using a previously defined methodology developed by the RIBEF Network to evaluate studies on Central American healthy volunteers [32]. The search included a selected panel of 121 pharmacogenetic biomarkers (see Supplemental data, Table 1). The search terms were “Mexico” and “pharmacogenetic biomarker”, looked up one by one, for genotype studies and “probe drugs” and “Mexico” for phenotype reports exploration. The probe drugs searched were debrisoquine, sparteine, metoprolol, dextromethorphan, mephenytoin, omeprazole, tolbutamide, losartan, diclofenac, isoniazid and caffeine. From these quests, studies were further selected according to the following inclusion criteria: (i) studies reporting genotype, allele and/or metabolic phenotype frequencies for one or more of the biomarkers revised; (ii) only unrelated healthy volunteers included in the reports; and (iii) subjects studied originated from Mexico, either indigenous or mestizo populations (Figure 1). It also considers Mexican populations living in the United States, as a result of migration, who have complete Mexican linage and in whom pharmacogenetic studies have been performed. Studies in which the frequencies were calculated from control groups as of case-control studies were excluded from this review. All allele frequencies reported in this review correspond to the mutant variant. Frequencies of the wild-type alleles CYP2D6*1, CYP2C9*1 and CYP2C19*1 were not considered because these alleles are determined by the absence of other CYP2D6, CYP2C9 and CYP2C19 polymorphisms, and consequently, it depends on the number of the polymorphisms studied in the original article.

Flow diagram of search methodology [33].
Figure 1:

Flow diagram of search methodology [33].

The “predicted” phenotype from genotype was assessed for CYP2D6, CYP2C9, CYP2C19 and NAT2 genes. Individual carriers of three CYP2D6 inactive alleles (CYP2D6*3, *4 and *5) were classified as poor metabolizers (gPMs), and those with more than two active CYP2D6 genes were classified as predicted ultrarapid metabolizers (gUMs), according to previously published methods [34, 35]. Individuals homozygous for the alleles with decreased enzyme activity of CYP2C9 (e.g. CYP2C9*2 and/or CYP2C9*3) [36] were also identified as gPMs as well as those individuals homozygous for the null alleles CYP2C19*2 and/or *3. For CYP2C19, the “predicted” ultrarapid metabolism was assigned as homozygous for the CYP2C19*17 variant [37]. Finally, subjects with two NAT2 alleles related to a decreased in vivo activity (e.g. NAT2*5A-*5J, *6A-*6D, *14A-*14G) were classified as slow acetylators (gSAs) [38]. The “predicted” phenotypes from genotype and allelic frequencies were calculated from original raw data whenever this information was not included in the corresponding publication.

The frequencies were compared with the weighted average of the frequencies calculated for the remaining groups, and to calculate the weighted average, the total number of subjects studied was taken into account. The differences among allele, genotype and phenotype frequencies of MM and MI (MM vs. MM, MI vs. MI and MM vs. MI) from different states of Mexico were analyzed using the χ2 test with the Epi Info™ 7.1.5 software (Centers for Disease Control and Prevention, Atlanta, GA, USA). The p-values <0.05 were considered statistically significant.


A total of 63 studies were included in the present review, wherein 56,292 healthy volunteers were genotyped for one or more of 31 pharmacogenetic biomarkers. Most of these individuals (71.58%) were MMs from different Mexican states, whereas the rest corresponded to various MI groups. Figure 2 shows the location of MM and MI populations within the United Mexican States where pharmacogenetic studies were performed. In addition, a study of MMs living in Los Angeles, CA, USA, was included because it met the inclusion criteria, and individuals with at least three Mexico-born grandparents were involved [39]. Only seven studies included ancestry information based on HLA alleles [40], THO1 marker [41], ancestry informative markers [4244] and STRs [45, 46].

Map of United Mexican States. Gray regions are the states where at least one study of pharmacogenetic biomarkers in Mexican Mestizo healthy volunteers has been performed. Arabic numbers indicate the states where healthy volunteers from Mexican indigenous groups have been studied.
Figure 2:

Map of United Mexican States. Gray regions are the states where at least one study of pharmacogenetic biomarkers in Mexican Mestizo healthy volunteers has been performed.

Arabic numbers indicate the states where healthy volunteers from Mexican indigenous groups have been studied.

Allele frequencies of pharmacogenetic biomarkers in Mexican populations

Reports of frequencies for 31 pharmacogenetic biomarkers in healthy MM or MI populations were found, namely, CYP2D6, CYP2C9, CYP2C19, CYP1A1, CYP1A2, CYP2B6, CYP3A4, CYP3A5, NAT2, TPMT, MTHFR, UGT1A1, UGT1A4, COMT, EPHX1, GSTM1, GSTP1, GSTT1, HLA-A, HLA-B, ABCB1, ABCG2, TP53, XRCC1, EGFR, ERBB2, ERCC1, CCR5, F5, G6PD and VKORC1.

Frequencies of studied CYP2D6 alleles are shown in Table 1. Currently, more than 100 CYP2D6 variants have been described [54]; however, only 14 have been studied in seven MM populations and 13 MI groups. The average frequencies in MM populations of the CYP2D6 null alleles *3, *4 and *5; the decreased enzymatic activity *10, *17 and *41 alleles; and the standard activity *35 allele showed differences with the MI groups (χ2 test, p<0.05). No differences were found in the frequencies of CYP2D6 alleles in the two studies for MMs from Chiapas reported.

Table 1

CY2D6 allele frequencies in healthy volunteers from different Mexican populations.

Important differences in CYP2C9*2 and *3 decreased activity alleles’ frequencies were found between MM and MI groups because of the higher prevalence of these alleles in MM compared with MI populations (χ2 test, p<0.001) (Table 2). CYP2C9*3 frequencies were different between the two MM studies from the Mexico City Area (χ2 test, p<0.05), and also between the two studies in Tarahumara (χ2 test, p<0.05). In regard to CYP2C19 alleles, only the CYP2C19*2 null activity variant has been found among Mexican populations, whereas the recent CYP2C19*17 variant, related with high enzymatic activity, has only been studied in MM populations (Table 2). No differences were observed between average CYP2C19 allele frequencies of MM and MI groups. The frequencies of CYP2C19*2 allele reported for the two studies of MMs from the Mexico City Area were similar (χ2 test, p>0.05).

Table 2

CYP2C9 and CYP2C19 alleles’ frequencies in healthy volunteers from different Mexican populations.

With regard to other CYPs, studies have determined the frequencies of CYP1A1, CYP1A2, CYP2B6, CYP3A4 and CYP3A5 alleles (Table 3). Frequencies higher than 50% were found for at least one variant of these CYPs. The CYP1A1*2C frequency reported for 96 MMs from the Mexico City Area was lower than those estimated in two studies of MMs from the same area.

Table 3

Allele frequencies of other CYP450 alleles in healthy volunteers from different Mexican populations.

Frequencies of NAT2, TPMT, MTHFR, UGT1A1, UGT1A4, COMT, EPHX1, GSTM1, GSTP1 and GSTT1 variants are shown in Table 4. The frequencies of all these polymorphic genes have been determined in MM populations, whereas only MTHFR and GSTP1 have also been studied in MI groups. The frequencies of MTHFR polymorphisms and GSTP1 variant were statistically different between MM and MI groups (χ2 test, p<0.05). Also, the frequencies reported for GSTP1 p.Ile105Val polymorphism in the two studies of MMs from Mexico City Area were statistically different (χ2 test, p<0.05).

Table 4

Allele frequencies of polymorphisms in other drug metabolizing enzymes in healthy volunteers from different Mexican populations.

The frequencies of HLA alleles that have been reported as pharmacogenetic biomarkers are shown in Table 5. Among these, HLA-B*57:01 and HLA-B*58:01 have been predominantly studied in MM and MI groups. The average frequency of HLA-A*31:01 allele was different between the studied MM and MI groups (χ2 test, p<0.05).

Table 5

Frequencies of HLA alleles considered as pharmacogenetic biomarkers in healthy volunteers from different Mexican populations.

Regarding the frequencies in genes encoding transporters, the variant rs2231142 (Q141K) of ABCG2 gene has only been studied in MMs from Los Angeles, CA, for which a 20.00% frequency was reported [39]. The frequency of the ABCB1 polymorphism rs1045642 (C3435T) described in MMs from Jalisco (60.00%, n=111) was higher than those reported in two studies of MMs from Mexico City Area (47.70%, n=269 and 51.00%, n=300, respectively) and from the report in MMs from Los Angeles (48.00%, n=93) (χ2 test, p<0.01) [39, 56, 58, 88]. For the variants rs2032582 (G2677T/A) and rs1128503 (C1236T) of ABCB1, only one report was found in MMs, and the allele frequencies were 42.00% T and 7.00% A for the 2677T/A variant and 50.00% for the 1236T polymorphism [58].

For the following pharmacogenetic biomarkers, only one report was found describing allele frequencies in Mexican healthy volunteers for each case: TP53 p.72P (rs1042522, R72P) in 36.00% of 382 MMs from Mexico City Area [64], XRCC1 p.399Q (rs25487, R399Q) in 25.00% of 382 MMs from Mexico City Area [64, 65], EGFR p.521K (rs2227983, R521K) and ERBB2 p.655V (rs1136201, I655V) in 29.50% and 14.10% of 103 MMs from Western Mexico, respectively [89], and ERCC1 c.354C (rs11615, N118N) in 30.00% of 91 MMs from Los Angeles, CA [39]. Factor V Leiden (F5) was not found in any of 100 MM healthy volunteers from Mexico City Area [90]. The deletion in CCR5 gene has been reported for 4.40% of MMs from Nuevo León (n=103) [91], 3.00% of MMs from Yucatán (n=242) [92], and 1.60% of Mazatecos (n=61), and it was not found in Mayos (n=70) and Teeneks (n=61) [93]. A higher frequency of CCR5 deletion was observed in MM populations in comparison to that reported for MI groups (χ2 test, p<0.05).

Glucose-6-phosphate dehydrogenase (G6PD) deficiency, calculated with enzymatic assays, in 4777 MM healthy volunteers belonging to four states of the Pacific Coast (Sinaloa, Nayarit, Colima and Guerrero), three states of the Gulf of Mexico (Tamaulipas, Veracruz and Yucatan) and three northeastern states (San Luis Potosi, Coahuila and Durango) showed an average prevalence of 0.71%, suggesting that 1:140 males of the general population is G6PD deficient and consequently has a potential risk for the development of hemolysis in the presence of precipitating factors [94]. A similar G6PD deficiency frequency (0.77%) had been previously identified in 1938 MM individuals from the same four states of the Pacific Coast [95]. However, a slightly higher G6PD deficiency frequency (0.95%) was recently reported in 1993 MM subjects from four Northern States (Sonora, Baja California, Baja California Sur and Chihuahua) [96]. In contrast to the aforementioned studies, a much smaller frequency of 0.19% was recently determined in 21,619 MM newborns from a public hospital in Mexico City [97]. With regard to mutations implicated in G6PD deficiency, G6PDA-202A/376G and G6PDA-376G/468C genotype frequencies reported in MMs ranged from 48.78% to 78.57% and from 3.57% to 14.63%, respectively [9497].

Two studies have determined the frequencies of VKORC1 variants and haplotypes in MM and MI healthy volunteers [26, 44]. The polymorphisms determined were rs3673 (g.45261860C>T), rs6484 (c.*1742_*1743insTGTTG), rs5808 (c.*664G>C), rs6853 (c.*1727A>G), rs7566 (c.*804T>C), rs381 (g.31927369C>T), rs9041 (c.*2426G>T), and rs11150606 (p.Gln30Arg) (data not shown). Reported frequencies of VKORC1 haplotypes showed that H1 was present in 6.00%–36.00% of MMs from Guanajuato, Guerrero, Zacatecas, Veracruz, Sonora and Yucatán and 0.00%–51.40% in MI groups as Mayas, Tepehuanos, Zapotecos and Mixtecos. Haplotype H2 was found in 5.00%–19.00% of MMs and 0.70%–2.00% of MI. Haplotypes H7 and H8 were reported in 35.00%–51.00% of MMs and 44.00%–53.10% of MI, whereas haplotype H9 was found in 8.00% of MMs but was absent in MI [26, 44]. Other VKORC1 haplotypes have been reported, and some of them are found in a low frequency among Mexican populations as H3, H4 and H5 (<3.00%), whereas haplotypes H1–H9 were found in more than the 95.00% of MM and MI populations [26].

Studies on frequencies of “predicted” phenotype from genotype and “measured” phenotype

The frequencies of gPMs, gUMs and mPMs for CYP2D6; gPMs for CYP2C9; gPMs, gUMs, mPMs and mUMs for CYP2C19; and gSAs and mSAs for NAT2 and the frequencies of individuals homozygous or heterozygous for TPMT deficiency alleles determined in Mexican populations are shown in Table 6. The average frequencies of gPMs and mPMs of CYP2D6 and the gPMs of CYP2C9 were higher in MM than in MI groups (χ2 test, p<0.05). In addition, for CYP3A4, one study that used omeprazole as probe drug reported a frequency of 11% of mPMs in 127 West Mexicans [99]. Omeprazole is not widely used as a probe drug for CYP3A4; however, the authors of this study considered that measuring the log of omeprazole/omeprazole sulfone is useful for the evaluation of CYP3A4 metabolic capacity. “Measured” phenotype has only been studied in four MM populations and one MI group. No information was found for the probe drugs debrisoquine, sparteine, metoprolol, mephenytoin, tolbutamide, losartan, diclofenac and caffeine.

Table 6

Frequencies of “predicted” phenotypes from genotype and “measured” phenotype reported for Mexicans healthy volunteers.


From the list of 121 pharmacogenetic biomarkers, 31 (25.62%) have been studied in Mexican healthy volunteers that represent 5.01E-4 of the total Mexico’s population. This number is higher than the pharmacogenetic biomarkers previously reported for Central American healthy volunteers (12/104, 11.54%) [32]. The other two previous reports in Mexico were performed using a different literature search strategy than the one used in the present study, and they only described the frequencies of seven [30] and six [31] drug metabolizing biomarkers, respectively.

In the majority of Mexican states, at least one study was found, including pharmacogenetic biomarker frequency. However, in four Mexican states (Aguascalientes, Querétaro, Campeche and Quintana Roo), pharmacogenetic data are still missing. It is also necessary to enlarge this type of investigation where there is scarce information. For instance, individuals in several MI groups have been studied in Oaxaca, but MMs have not been studied. It would be of interest to compare the frequencies among these populations. Similarly, in Veracruz, only MMs have been studied, and there are many indigenous groups that have not been included in pharmacogenetic investigations [100].

It is well documented that frequencies of CYP2D6 alleles and its metabolic phenotypes present interethnic variability [12]. In regard to Mexico, MMs from Durango and Mayos and Seris populations present a lower frequency of CYP2D6*2 than the rest of Mexican populations, whereas a higher frequency of this allele was found among MMs from Sonora and Coras. CYP2D6 allele multiplications were reported in a high frequency for MMs from Mexico City Area and for Huicholes. Interestingly, a high variability in frequencies of the CYP2D6*4 null allele was found in the studied MI populations, whereas CYP2D6*7, *8, *53, and *82 have been scarcely studied among Mexican populations (Table 1).

Research of the CYP2D6 “measured” phenotype in MMs showed that 6.80%–10.00% are mPMs, whereas the “predicted” phenotype studies reported <6.00% gPMs in MM populations and nearly none in MI. gUMs were found in both MM and MI populations, with frequencies as high as 20% for Guarijíos and Huicholes (Table 6). Variations on CYP2D6 metabolism could have clinical implications in the therapy of drugs as tamoxifen and codeine. Tamoxifen is frequently used for the prevention and treatment of estrogen receptor (ER)-positive breast cancer. Tamoxifen is a prodrug that requires metabolic activation to exert its pharmacological activity. CYP2D6 is the enzyme related to the conversion of tamoxifen into its active metabolite 4-hydroxytamoxifen. It has been found that in CYP2D6 PMs, an increased risk for breast cancer relapse is present [101].

Codeine is an opioid analgesic indicated for the relief of mild to moderately severe pain. The analgesic properties of codeine are related to its conversion to morphine by CYP2D6. The percentage of codeine converted to morphine can be much higher in UMs that are at risk of severe toxicity. Current evidence supports that PMs have the possibility of lack of effect, and therefore, the avoidance of codeine use is recommended [102, 103].

The CYP2C9*2 and *3 alleles were the two most studied CYP2C9 alleles in Mexican healthy volunteers. The frequencies of these alleles were statistically higher in MM than in MI populations, probably due to the influence of Caucasian populations in admixture process and/or the Oriental genetic background in Amerindian populations [45, 57, 104]. The highest frequencies of CYP2C9*2 were observed for MM and MI populations from the northern states of Mexico (Nuevo León, Sonora, Zacatecas, Mayos and Tarahumara). Differences observed between the CYP2C9*3 frequencies reported for the two MM populations from Mexico City Area [58, 59] could be due to the different genotyping methods (PCR restriction fragment length polymorphism and real-time PCR) or the sample size (300 vs. 947) reported for MM groups. However, there is not a clear explanation for the difference between the two studies in Tarahumara [45, 59]. The frequency of gPMs was relatively low for MM and MI populations (≤2.10%) (Table 6), and the lack of studies on the CYP2C9 “measured” phenotype does not allow to consider if CYP2C9 genotyping is important for the drug dosage of CYP2C9 substrates in Mexico.

For CYP2C19, the main differences on allele frequencies were found among the different MI groups, with the highest frequency of the CYP2C19*2 allele, related to null enzymatic activity, present in Tarahumara from Chihuahua (31.00%) and the lowest in Purépechas from Michoacán (5.40%) and Tojolabales and Tzeltales from Chiapas (3.60% and 0.00%, respectively) (Table 2). Moreover, it is important to highlight the absence of the other null activity allele CYP2C19*3 in all the included Mexican populations studies. Both CYP2C19 PMs and UMs have been reported for MI and MM populations, with the highest frequencies of gPMs reported for MMs from Jalisco (6.30%) and Tarahumara (10.70%), whereas the only study of “measured” phenotype in healthy volunteers reported 6.00% of mPMs and 4.00% of mUMs in Jalisco (Table 6). The clinical impact of CYP2C19 poor and ultrarapid metabolism might be observed with clopidogrel. This is a potent antiplatelet drug indicated for the prevention of vascular thrombotic events in patients at risk, such as myocardial infarction, coronary artery disease and stroke. Clopidogrel is a prodrug, which is first oxidized to a 2-oxo-clopidogrel intermediate metabolite. The subsequent metabolism of this intermediate metabolite results in the formation of the active metabolite, a thiol derivative of clopidogrel that irreversibly blocks the platelet P2Y12 receptor, thereby inhibiting ADP-induced platelet aggregation. The main enzyme that is associated to its metabolism is CYP2C19. It has been found that the genetic variants CYP2C19*2, *3, *4, or *5, related to a PM phenotype, are associated with an increased risk of cardiovascular events such as death, heart attack and stroke in patients taking clopidogrel [105]. The FDA and the EMA have included a warning on clopidogrel (Plavix) to make patients and health care providers aware that CYP2C19 PMs are at high risk of treatment failure and that testing is available [106, 107].

Studies of NAT2 allele’s frequencies in healthy volunteers have been only performed in MMs from Baja California and San Luis Potosí. NAT2 variants related to a slow metabolism (e.g. *5, *6, *7) were found in a high frequency among the studied MM populations (>30.00%) (Table 4). Furthermore, 68.00% of MMs from Baja California were identified as mSAs (Table 6). Although there are only three studies of NAT2 in MM and none in MI populations, it is important to take into account the high prevalence of the SA phenotype, especially for drugs such as isoniazid, an important agent in the treatment of tuberculosis in combination with other drugs or alone as a prophylactic agent. Pharmacogenetic research has indicated that isoniazid concentrations as well as efficacy and toxicity of isoniazid are linked to the activity of the NAT2 enzyme. SAs are at greater risk to develop hepatotoxicity compared with rapid acetylators [108]. This evidence could be useful to improve the safety of isoniazid therapy.

The great number of frequencies reported for MTHFR polymorphisms in several Mexican populations also allows observing the interethnic variability among them (Table 4). In general, there is a high 677T allele frequency among the studied Mexican populations, with the highest frequencies observed in MI (46.30%–92.20%) and the lowest (38.00%–47.00%) present in MMs from Northern States of Mexico (Nuevo León, Baja California and Sonora), as it has been previously described [43, 109]. Nevertheless, the frequency of this allele in Mexican populations is greater to that reported in some European (<35.00% in Spain, the Netherlands, Hungary and Russia) and African (0.00%–3.00%) populations [110], which could be due to an enrichment of this variant in Mexicans as a result of the admixture process and the Amerindian background [43].

According to the studies reviewed here, frequencies of TPMT deficiency alleles were reported in up to 5.69% of the MMs from Mexico City Area, and individual carriers of at least one copy of a deficiency allele (*2, *3A, *3B and *3C) account for more than 10.00% of MM population (Table 4). The differences in the frequencies of TPMT*3B alleles between the two studies in MMs from Mexico City Area may be due to the dissimilar genotyping methodologies used in the studies (DHPLC analysis and PCR restriction fragment length polymorphism) [45, 46]. This enzyme plays an important role in the metabolism of thiopurine drugs as 6-mercaptopurine (6-MP), an analog of the purine bases adenine and hypoxanthine, used as immunosuppressant in the treatment of autoimmune disorders, inflammatory bowel disease, debilitating skin diseases and various inflammatory eye conditions, as well as an antiproliferative drug in childhood acute lymphoblastic leukemia. 6-MP is inactivated via two major pathways. In one of them, a thiol methylation, catalyzed by the enzyme TPMT, forms the inactive metabolite methyl-6-MP, which prevents 6-MP from further conversion into active, cytotoxic thioguanine nucleotide (TGN) metabolites. Patients homozygous for TPMT deficiency alleles with little or no detectable TPMT activity, receiving standard doses of 6-MP, accumulate excessive cellular concentrations of active TGNs predisposing them to 6-MP toxicity. Also, heterozygous patients with low or intermediate TPMT activity accumulate higher concentrations of active 6-TGNs than patients with normal TPMT activity and are more likely to experience 6-MP toxicity [111]. The FDA and the EMA-approved label for 6-MP recommend testing for TPMT activity in patients with clinical or laboratory evidence of severe bone marrow toxicity, or repeated episodes of myelosuppression [112, 113].

Only one study on UGT1A1*28 in healthy volunteers was found for Mexican populations. The frequency reported was 36.00%, and it was calculated from Mexicans living in Los Angeles, CA (Table 4). This allele results from seven TA repeats in the promoter region of UGT1A1 (TATA box) that reduces transcription efficiency, lowers the enzyme concentrations, and thus leads to the accumulation of substrates [114]. Irinotecan is a derivative of camptothecin, primarily used in the treatment of metastatic colorectal cancer. The drug is subject to a great interindividual variability in pharmacokinetic behavior, treatment efficacy, and the occurrence of unpredictable, sometimes severe, toxic side effects that might be life threatening in some patients. It has been recognized that inherited differences in the metabolism can affect the efficacy and toxicity of the drug. The risk of severe irinotecan-associated neutropenia is related in part to presence of the UGT1A1*28 variant, which is linked to reduced elimination of the irinotecan active metabolite SN-38 [115]. The FDA labeling of irinotecan includes a warning of greater neutropenia risk in those patients with reduced activity in the UGT1A1 enzyme [116]. Recently, a decision tree for UGT1A1 genotyping depending on initially intended irinotecan dose has been described in France to secure irinotecan administration [117].

Warfarin is an oral anticoagulant with narrow therapeutic index and commonly prescribed in Mexico for the prevention of thrombosis and thromboembolism. The drug is supplied as a racemic mixture of R- and S-enantiomer; however, S-warfarin is more potent at inhibiting vitamin K reductase. It has been shown that variations in two genes are related with the individual response to warfarin dosing. One gene is CYP2C9, which metabolizes S-warfarin into its inactive form (S-7-hydroxywarfarin). The other gene, VKORC1 (VKOR complex subunit 1), plays a major role in the vitamin K pathway and is the target protein of warfarin. It has been found that individual carriers of the decreased activity variants CYP2C9*2 and CYP2C9*3 are more likely to need lower doses of warfarin and have an increased risk of bleeding complications. With regard to VKORC1, it has been shown that when the common G allele is replaced by the A allele (-1639G>A), lower warfarin doses are needed to inhibit VKORC1 and to produce an anticoagulant effect. Recently, the FDA stated that the patient’s CYP2C9 and VKORC1 genotype information, when available, can assist in the selection of the starting dose [118, 119]. Previously, the low frequency of CYP2C9*2 and *3 alleles found in Mexican populations was mentioned; however, the VKORC1 polymorphisms are highly prevalent in these populations. According to a recent report from MM and MI populations, 67% of MMs and 71% of MI are carriers of at least one copy of the -1639A allele and would better respond to a lower dose of warfarin [26].

It is important to highlight the significant variation on the frequencies reported in three studies for the COMT polymorphism, in which two of them were performed in the Mexico City Area. These controversial data warrant further investigations in MM and MI populations, where studies are absent. Similarly, a lack of information in MI was observed for G6PD deficiency, whereas the frequency in MMs determined in one study [97] contrasts to the frequencies reported in the other three investigations [9496], probably due to the difference on the number of individuals studied.

HLA molecules show particularly high polymorphism with a great worldwide variability, and alleles that are highly frequent in one group being scant or even absent in others [81]. The variation on HLA alleles’ frequencies described in this review are noticeable (Table 5); however, the clinical implication of all these alleles in Mexicans has not been determined. A recent report found a relation between HLA-A*31:01:02 allele with cutaneous adverse drug reaction induced by carbamazepine [83]. The frequency of this allele in MMs varies from 2.40% to 8.25%, but in MI, the frequency reaches values of 19.80% in mixes from Oaxaca. In countries ethnically admixed such as Mexico, the genetic structure varies from one region to another. Therefore, pharmacogenetic studies in different populations are necessary to determine the biomarkers’ frequencies corresponding to each region or ethnic group that could predict adverse drug reactions or help to personalize therapies.

The data described in the present study represent a valuable knowledge about the frequencies of pharmacogenetic biomarkers reported in MM and MI populations, where a significant frequency variation between these populations was found in several cases. In addition, it highlights the need to perform this type of study in some MM and MI populations where information is lacking.

Pharmacogenetic biomarkers will remain to accumulate in the future when its clinical significance is established. At present, the FDA and the EMA provide pharmacogenetic information in some drug labels to provide information to health care professionals. The data obtained in the present review show the presence of relevant frequencies of pharmacogenetic biomarkers, such as CYP2D6, CYP2C19, NAT2 and VKORC1, in MM and MI populations. Taking into account this information, we consider that it would be of interest that pharmacogenetic information in Mexico could be added in the labels of those drugs that are commonly used in our country, where relevant frequencies of biomarkers are found in Mexican populations, and for which clinical pharmacogenetic studies show that their use is important to improve drug efficacy and safety. Therefore, routine screening for pharmacogenetic biomarkers in the Mexican health care system should be analyzed in light of the biomarker prevalence in Mexican populations and the cost-benefit of its implementation.

Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

Research funding: This research was supported by a grant from Consejo Nacional de Ciencia y Tecnología de México (CONACyT) (#167261) and by Junta de Extremadura, AEXCID 13IA001 (to SIFF) and coordinated by the network Red Iberoamericana de Farmacogenética y Farmacogenómica (www.ribef.com). IFG was supported by a scholarship (Doctor’s degree) from CONACyT (#369708).

Employment or leadership: None declared.

Honorarium: None declared.

Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.


  • 1.

    Evans WE, Mcleod HL. Pharmacogenomics – drug disposition, drug targets, and side effects. N Engl J Med 2003;348:538–49. Google Scholar

  • 2.

    Evans WE, Johnson JA. Pharmacogenomics: the inherited basis for interindividual differences in drug response. Annu Rev Genomics Hum Genet 2001;2:9–39.Google Scholar

  • 3.

    Evans WE, Relling MV. Pharmacogenomics: translating functional genomics into rational therapeutics. Science 1999;286:487–91.Google Scholar

  • 4.

    McLeod HL, Evans WE. Pharmacogenomics: unlocking the human genome for better drug therapy. Annu Rev Pharmacol Toxicol 2001;41:101–21. Google Scholar

  • 5.

    FDA. Genomics – Table of pharmacogenomic biomarkers in drug labeling [Internet]. Center for Drug Evaluation and Research. Food and Drug Administration [cited 2015 Jun 16]. Available from: http://www.fda.gov/drugs/scienceresearch/researchareas/pharmacogenetics/ucm083378.htm

  • 6.

    ICH Topic E15 Definitions for Genomic Biomarkers, Pharmacogenomics, Pharmacogenetics, Genomic Data and Sample Coding Categories [Internet]. 2007 [cited 2015 Jun 16]. Available from: http://www.ema.europa.eu/docs/en_GB/document_library/.

  • 7.

    Ehmann F, Caneva L, Prasad K, Paulmichl M, Maliepaard M, Llerena A, et al. Pharmacogenomic information in drug labels: European Medicines Agency perspective. Pharmacogenomics J 2015;15:201–10. Google Scholar

  • 8.

    LLerena A, Berecz R, Dorado P, González AP, Peñas-LLedó EM, De La Rubia A. CYP2C9 gene and susceptibility to major depressive disorder. Pharmacogenomics J 2003;3:300–2. Google Scholar

  • 9.

    Peñas-Lledó E, Guillaume S, Naranjo ME, Delgado A, Jaussent I, Blasco-Fontecilla H, et al. A combined high CYP2D6-CYP2C19 metabolic capacity is associated with the severity of suicide attempt as measured by objective circumstances. Pharmacogenomics J 2015;15:172–6.Google Scholar

  • 10.

    Peñas-Lledó EM, Blasco-Fontecilla H, Dorado P, Vaquero-Lorenzo C, Baca-García E, Llerena A. CYP2D6 and the severity of suicide attempts. Pharmacogenomics 2012;13:179–84. Google Scholar

  • 11.

    Suarez-Kurtz G, Paula DP, Struchiner CJ. Pharmacogenomic implications of population admixture: Brazil as a model case. Pharmacogenomics 2014;15:209–19. Google Scholar

  • 12.

    LLerena A, Naranjo ME, Rodrigues-Soares F, Penas-LLedó EM, Fariñas H, Tarazona-Santos E. Interethnic variability of CYP2D6 alleles and of predicted and measured metabolic phenotypes across world populations. Expert Opin Drug Metab Toxicol 2014;10:1569–83. Google Scholar

  • 13.

    Sistonen J, Fuselli S, Palo JU, Chauhan N, Padh H, Sajantila A. Pharmacogenetic variation at CYP2C9, CYP2C19, and CYP2D6 at global and microgeographic scales. Pharmacogenet Genomics 2009;19:170–9. Google Scholar

  • 14.

    Teh LK, Hashim H, Zakaria ZA, Salleh MZ. Polymorphisms of UGT1A1*6, UGT1A1*27 & UGT1A1*28 in three major ethnic groups from Malaysia. Indian J Med Res 2012;136:249–59. Google Scholar

  • 15.

    Lonjou C, Thomas L, Borot N, Ledger N, de Toma C, LeLouet H, et al. A marker for Stevens-Johnson syndrome…: ethnicity matters. Pharmacogenomics J 2015;6:265–8. Google Scholar

  • 16.

    Yip VL, Marson AG, Jorgensen AL, Pirmohamed M, Alfirevic A. HLA genotype and carbamazepine-induced cutaneous adverse drug reactions: a systematic review. Clin Pharmacol Ther 2012;92:757–65.Google Scholar

  • 17.

    Aihara M. Pharmacogenetics of cutaneous adverse drug reactions. J Dermatol 2011;38:246–54.Google Scholar

  • 18.

    Kaniwa N, Sugiyama E, Saito Y, Kurose K, Maekawa K, Hasegawa R, et al. Specific HLA types are associated with antiepileptic drug-induced Stevens-Johnson syndrome and toxic epidermal necrolysis in Japanese subjects. Pharmacogenomics 2013;14:1821–31. Google Scholar

  • 19.

    Gan GG, Phipps ME, Lee MMT, Lu LS, Subramaniam RY, Bee PC, et al. Contribution of VKORC1 and CYP2C9 polymorphisms in the interethnic variability of warfarin dose in Malaysian populations. Ann Hematol 2011;90:635–41. Google Scholar

  • 20.

    Chan SL, Suo C, Lee SC, Goh BC, Chia KS, Teo YY. Translational aspects of genetic factors in the prediction of drug response variability: a case study of warfarin pharmacogenomics in a multi-ethnic cohort from Asia. Pharmacogenomics J 2012;12:312–8.Google Scholar

  • 21.

    Shimoyama S. Pharmacogenetics of irinotecan: an ethnicity-based prediction of irinotecan adverse events. World J Gastrointest Surg 2010;2:14–21. Google Scholar

  • 22.

    Sosa-Macias M, Moya GE, LLerena A, Ramírez R, Terán E, Peñas-LLedó EM, et al. Population pharmacogenetics of Ibero-Latinoamerican populations (MESTIFAR 2014). Pharmacogenomics 2015;16:1–4. Google Scholar

  • 23.

    INEGI. Número de habitantes. Cuéntame de México [Internet]. 2015 [cited 2015 Jun 18]. Available from: http://cuentame.inegi.org.mx/poblacion/habitantes.aspx?tema=P

  • 24.

    Jimenez-Sanchez G, Silva-Zolezzi I, Hidalgo A, March S. Genomic medicine in Mexico: initial steps and the road ahead. Genome Res 2008;18:1191–8. Google Scholar

  • 25.

    Moreno-Estrada A, Gignoux CR, Fernández-López JC, Zakharia F, Sikora M, Contreras AV, et al. Human genetics. The genetics of Mexico recapitulates Native American substructure and affects biomedical traits. Science 2014;344:1280–5. Google Scholar

  • 26.

    Villegas-Torres B, Sánchez-Girón F, Jaramillo-Villafuerte K, Soberón X, Gonzalez-Covarrubias V. Genotype frequencies of VKORC1 and CYP2C9 in native and Mestizo populations from Mexico, potential impact for coumarin dosing. Gene 2015;558:235–40. Google Scholar

  • 27.

    Acuña-Alonzo V, Flores-Dorantes T, Kruit JK, Villarreal-Molina T, Arellano-Campos O, Hünemeier T, et al. A functional ABCA1 gene variant is associated with low HDL-cholesterol levels and shows evidence of positive selection in Native Americans. Hum Mol Genet 2010;19:2877–85. Google Scholar

  • 28.

    Williams AL, Jacobs SB, Moreno-Macías H, Huerta-Chagoya A, Churchhouse C, Márquez-Luna C, et al. Sequence variants in SLC16A11 are a common risk factor for type 2 diabetes in Mexico. Nature 2014;506:97–101. Google Scholar

  • 29.

    Silva-Zolezzi I, Hidalgo-Miranda A, Estrada-Gil J, Fernandez-Lopez JC, Uribe-Figueroa L, Contreras A, et al. Analysis of genomic diversity in Mexican mestizo populations to develop genomic medicine in Mexico. Proc Natl Acad Sci USA 2009;106:8611–6. Google Scholar

  • 30.

    Cuautle-Rodríguez P, Llerena A, Molina-Guarneros J. Present status and perspective of pharmacogenetics in Mexico. Drug Metabol Drug Interact 2014;29:37–45. Google Scholar

  • 31.

    Sosa-Macías M, Llerena A. Cytochrome P450 genetic polymorphisms of Mexican indigenous populations. Drug Metabol Drug Interact 2013;28:193–208. Google Scholar

  • 32.

    Céspedes-Garro C, Naranjo M-E, Ramírez R, Serrano V, Fariñas H, Barrantes R, et al. Pharmacogenetics in Central American healthy volunteers: interethnic variability. Drug Metabol Personal Ther 2015;30:19–31. Google Scholar

  • 33.

    Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. J Clin Epidemiol 2009;62:1006–12. Google Scholar

  • 34.

    Gaedigk A, Simon SD, Pearce RE, Bradford LD, Kennedy MJ, Leeder JS. The CYP2D6 activity score: translating genotype information into a qualitative measure of phenotype. Clin Pharmacol Ther 2008;83:234–42. Google Scholar

  • 35.

    Llerena A, Dorado P, Ramírez R, González I, Alvarez M, Peñas-Lledó EM, et al. CYP2D6 genotype and debrisoquine hydroxylation phenotype in Cubans and Nicaraguans. Pharmacogenomics J 2012;12:176–83. Google Scholar

  • 36.

    CYP2C9 allele nomenclature. The Human Cytochrome P450 (CYP) Allele Nomenclature Database. 2014. Google Scholar

  • 37.

    CYP2C19 allele nomenclature [Internet]. The Human Cytochrome P450 (CYP) Allele Nomenclature Database. [cited 2014 May 15]. Available from: http://www.cypalleles.ki.se/cyp2c19.htm

  • 38.

    Sabbagh A, Langaney A, Darlu P, Gérard N, Krishnamoorthy R, Poloni ES. Worldwide distribution of NAT2 diversity: implications for NAT2 evolutionary history. BMC Genet 2008;9:21. Google Scholar

  • 39.

    Marsh S, King CR, Van Booven DJ, Revollo JY, Gilman RH, McLeod HL. Pharmacogenomic assessment of Mexican and Peruvian populations. Pharmacogenomics 2015;16:441–8. Google Scholar

  • 40.

    Zúñiga J, Yu N, Barquera R, Alosco S, Ohashi M, Lebedeva T, et al. HLA class I and class II conserved extended haplotypes and their fragments or blocks in Mexicans: implications for the study of genetic diversity in admixed populations. PLoS One 2013;8:e74442. Google Scholar

  • 41.

    Gorodezky C, Alaez C, Vázquez-García MN, de la Rosa G, Infante E, Balladares S, et al. The genetic structure of Mexican mestizos of different locations: tracking back their origins through MHC genes, blood group systems, and microsatellites. Hum Immunol 2001;62:979–91. Google Scholar

  • 42.

    Sanchez-Giron F, Villegas-Torres B, Jaramillo-Villafuerte K, Silva-Zolezzi I, Fernandez-Lopez JC, Jimenez-Sanchez G, et al. Association of the genetic marker for abacavir hypersensitivity HLA-B*5701 with HCP5 rs2395029 in Mexican mestizos. Pharmacogenomics 2011;12:809–14. Google Scholar

  • 43.

    Binia A, Contreras AV, Canizales-Quinteros S, Alonzo VA, Tejero ME, Silva-Zolezzi I. Geographical and ethnic distribution of single nucleotide polymorphisms within genes of the folate/homocysteine pathway metabolism. Genes Nutr 2014;9:421. Google Scholar

  • 44.

    Bonifaz-Peña V, Contreras AV, Struchiner CJ, Roela RA, Furuya-Mazzotti TK, Chammas R, et al. Exploring the distribution of genetic markers of pharmacogenomics relevance in Brazilian and Mexican populations. PLoS One 2014;9:e112640. Google Scholar

  • 45.

    Sosa-Macías M, Lazalde-Ramos BP, Galaviz-Hernández C, Rangel-Villalobos H, Salazar-Flores J, Martínez-Sevilla VM, et al. Influence of admixture components on CYP2C9*2 allele frequency in eight indigenous populations from Northwest Mexico. Pharmacogenomics J 2013;13:567–72. Google Scholar

  • 46.

    Lazalde-Ramos BP, Martínez-Fierro M de la L, Galaviz-Hernández C, Garza-Veloz I, Naranjo ME, Sosa-Macías M, et al. CYP2D6 gene polymorphisms and predicted phenotypes in eight indigenous groups from northwestern Mexico. Pharmacogenomics 2014;15:339–48. Google Scholar

  • 47.

    López M, Guerrero J, Jung-Cook H, Alonso ME. CYP2D6 genotype and phenotype determination in a Mexican Mestizo population. Eur J Clin Pharmacol 2005;61:749–54. Google Scholar

  • 48.

    Sosa-Macías M, Elizondo G, Flores-Pérez C, Flores-Pérez J, Bradley-Alvarez F, Alanis-Bañuelos RE, et al. CYP2D6 genotype and phenotype in Amerindians of Tepehuano origin and Mestizos of Durango, Mexico. J Clin Pharmacol 2006;46:527–36. Google Scholar

  • 49.

    Sosa-Macías M, Dorado P, Alanis-Bañuelos RE, Llerena A, Lares-Asseff I. Influence of CYP2D6 deletion, multiplication, -1584C→G, 31G→A and 2988G→ a gene polymorphisms on dextromethorphan metabolism among Mexican tepehuanos and mestizos. Pharmacology 2010;86:30–6. Google Scholar

  • 50.

    Contreras AV, Monge-Cazares T, Alfaro-Ruiz L, Hernandez-Morales S, Miranda-Ortiz H, Carrillo-Sanchez K, et al. Resequencing, haplotype construction and identification of novel variants of CYP2D6 in Mexican mestizos. Pharmacogenomics 2011;12:745–56. Google Scholar

  • 51.

    Salazar-Flores J, Torres-Reyes LA, Martínez-Cortés G, Rubi-Castellanos R, Sosa-Macías M, Muñoz-Valle JF, et al. Distribution of CYP2D6 and CYP2C19 polymorphisms associated with poor metabolizer phenotype in five Amerindian groups and western Mestizos from Mexico. Genet Test Mol Biomarkers 2012;16:1098–104. Google Scholar

  • 52.

    López-López M, Peñas-Lledó E, Dorado P, Ortega A, Corona T, Ochoa A, et al. CYP2D6 genetic polymorphisms in Southern Mexican Mayan Lacandones and Mestizos from Chiapas. Pharmacogenomics 2014;15:1859–65. Google Scholar

  • 53.

    Perez-Paramo YX, Hernandez-Cabrera F, Dorado P, Llerena A, Muñoz-Jimenez S, Ortiz-Lopez R, et al. Interethnic relationships of CYP2D6 variants in native and Mestizo populations sharing the same ecosystem. Pharmacogenomics 2015;16:703–12. Google Scholar

  • 54.

    CYP2D6. The Human Cytochrome P450 (CYP) Allele Nomenclature Database [Internet]. [cited 2015 Jun 16]. Available from: http://www.cypalleles.ki.se/cyp2d6.htm

  • 55.

    Aguilar B, Rojas JC, Collados MT. Prevalence of CYP2C9 variants in the Mexican population. Arch Med Res. 2008;39:463. Google Scholar

  • 56.

    Vargas-Alarcón G, Ramírez-Bello J, de la Peña A, Calderón-Cruz B, Peña-Duque MA, Martínez-Ríos MA, et al. Distribution of ABCB1, CYP3A5, CYP2C19, and P2RY12 gene polymorphisms in a Mexican mestizos population. Mol Biol Rep 2014;41:7023–9. Google Scholar

  • 57.

    Dorado P, Sosa-Macias MG, Peñas-Lledó EM, Alanis-Bañuelos RE, Wong M-L, Licinio J, et al. CYP2C9 allele frequency differences between populations of Mexican-Mestizo, Mexican-Tepehuano, and Spaniards. Pharmacogenomics J 2011;11: 108–12. Google Scholar

  • 58.

    Ortega-Vázquez A, Dorado P, Fricke-Galindo I, Jung-Cook H, Monroy-Jaramillo N, Martínez-Juárez IE, et al. CYP2C9, CYP2C19, ABCB1 genetic polymorphisms and phenytoin plasma concentrations in Mexican-Mestizo patients with epilepsy. Pharmacogenomics J [Internet]. 2015 Jun 30 [cited 2015 Jul 9]; Available from: http://www.ncbi.nlm.nih.gov/pubmed/26122019

  • 59.

    Castelán-Martínez OD, Hoyo-Vadillo C, Sandoval-García E, Sandoval-Ramírez L, González-Ibarra M, Solano-Solano G, et al. Allele frequency distribution of CYP2C9 2 and CYP2C9 3 polymorphisms in six Mexican populations. Gene 2013;523:167–72. Google Scholar

  • 60.

    Favela-Mendoza AF, Martinez-Cortes G, Hernandez-Zaragoza M, Salazar-Flores J, Muñoz-Valle JF, Martinez-Sevilla VM, et al. Genetic variability of CYP2C19 in a Mexican population: contribution to the knowledge of the inheritance pattern of CYP2C19*17 to develop the ultrarapid metabolizer phenotype. J Genet 2015;94:3–7. Google Scholar

  • 61.

    Fragoso JM, Juárez-Cedillo T, Hernández-Pacheco G, Ramírez E, Zuñiga J, Izaguirre R, et al. Cytochrome P4501A1 polymorphisms in the Amerindian and Mestizo populations of Mexico. Cell Biochem Funct 2005;23:189–93. Google Scholar

  • 62.

    Montero R, Araujo A, Carranza P, Mejía-Loza V, Serrano L, Albores A, et al. Genotype frequencies of polymorphic GSTM1, GSTT1, and cytochrome P450 CYP1A1 in Mexicans. Hum Biol 2007;79:299–312. Google Scholar

  • 63.

    Pérez-Morales R, Castro-Hernández C, Gonsebatt ME, Rubio J. Polymorphism of CYP1A1*2C, GSTM1*0, and GSTT1*0 in a Mexican Mestizo population: a similitude analysis. Hum Biol 2008;80:457–65. Google Scholar

  • 64.

    Pérez-Morales R, Méndez-Ramírez I, Castro-Hernández C, Martínez-Ramírez OC, Gonsebatt ME, Rubio J. Polymorphisms associated with the risk of lung cancer in a healthy Mexican Mestizo population: application of the additive model for cancer. Genet Mol Biol 2011;34:546–52. Google Scholar

  • 65.

    Molina E, Pérez-Morales R, Rubio J, Petrosyan P, Cadena LH, Arlt VM, et al. The GSTM1null (deletion) and MGMT84 rs12917 (Phe/Phe) haplotype are associated with bulky DNA adduct levels in human leukocytes. Mutat Res 2013;758:62–8. Google Scholar

  • 66.

    Mendoza-Cantú A, Castorena-Torres F, Bermudez M, Martínez-Hernández R, Ortega A, Salinas JE, et al. Genotype and allele frequencies of polymorphic cytochromes P450 CYP1A2 and CYP2E1 in Mexicans. Cell Biochem Funct 2004;22:29–34. Google Scholar

  • 67.

    Castorena-Torres F, Mendoza-Cantú A, de León MB, Cisneros B, Zapata-Pérez O, López-Carrillo L, et al. CYP1A2 phenotype and genotype in a population from the Carboniferous Region of Coahuila, Mexico. Toxicol Lett 2005;156:331–9. Google Scholar

  • 68.

    Reyes-Hernández OD, Arteaga-Illán G, Elizondo G. Detection of CYP3A4*1B and CYP3A4*2 polymorphisms by RFLP. Distribution frequencies in a Mexican population. Clin Genet 2004;66: 166–8. Google Scholar

  • 69.

    Reyes-Hernández OD, Lares-Asseff I, Sosa-Macias M, Vega L, Albores A, Elizondo G. A comparative study of CYP3A4 polymorphisms in Mexican Amerindian and Mestizo populations. Pharmacology 2008;81:97–103. Google Scholar

  • 70.

    Díaz-Molina R, Cornejo-Bravo JM, Ramos-Ibarra MA, Estrada-Guzmán JD, Morales-Arango O, Reyes-Báez R, et al. Genotype and phenotype of NAT2 and the occurrence of adverse drug reactions in Mexican individuals to an isoniazid-based prophylactic chemotherapy for tuberculosis. Mol Med Rep 2008;1: 875–9. Google Scholar

  • 71.

    Ramos MA, Mares RE, Avalos ED, Hernández A, Hernández R, Lameda R, et al. Pharmacogenetic screening of N-acetyltransferase 2, thiopurine s-methyltransferase, and 5,10-methylene-tetrahydrofolate reductase polymorphisms in Northwestern Mexicans. Genet Test Mol Biomarkers 2011;15:351–5. Google Scholar

  • 72.

    Salazar-González R, Gómez R, Romano-Moreno S, Medellín-Garibay S, Núñez-Ruíz A, Magaña-Aquino M, et al. Expression of NAT2 in immune system cells and the relation of NAT2 gene polymorphisms in the anti-tuberculosis therapy in Mexican mestizo population. Mol Biol Rep 2014;41:7833–43. Google Scholar

  • 73.

    Taja-Chayeb L, Vidal-Millán S, Gutiérrez O, Ostrosky-Wegman P, Dueñas-González A, Candelaria M. Thiopurine S-methyltransferase gene (TMPT) polymorphisms in a Mexican population of healthy individuals and leukemic patients. Med Oncol 2008;25:56–62.Google Scholar

  • 74.

    González-Del Angel A, Bermúdez-López C, Alcántara-Ortigoza MA, Vela-Amieva M, Castillo-Cruz RA, Martínez V, et al. Thiopurine S-methyltransferase (TPMT) genetic polymorphisms in Mexican newborns. J Clin Pharm Ther 2009;34:703–8. Google Scholar

  • 75.

    Guéant-Rodriguez R-M, Guéant J-L, Debard R, Thirion S, Hong LX, Bronowicki J-P, et al. Prevalence of methylenetetrahydrofolate reductase 677T and 1298C alleles and folate status: a comparative study in Mexican, West African, and European populations. Am J Clin Nutr 2006;83:701–7.Google Scholar

  • 76.

    Aguirre-Rodríguez AA, Martínez-de Villarreal LE, Velazco-Campos MD, Sampallo-Hernández E, Esmer-Sánchez MD. Prevalence of polymorphism in the MTHRF gene in a population sample from Nuevo Leon, Mexico. Salud Publica Mex 2008;50:5–7.Google Scholar

  • 77.

    Juárez-Velázquez R, Canto P, Canto-Cetina T, Rangel-Villalobos H, Rosas-Vargas H, Rodríguez M, et al. Analysis of polymorphisms in genes (AGT, MTHFR, GPIIIa, and GSTP1) associated with hypertension, thrombophilia and oxidative stress in Mestizo and Amerindian populations of México. Dis Markers 2010;28:323–31.Google Scholar

  • 78.

    López M, Dorado P, Ortega A, Peñas-Lledó E, Monroy N, Silva-Zolezzi I, et al. Interethnic differences in UGT1A4 genetic polymorphisms between Mexican Mestizo and Spanish populations. Mol Biol Rep 2013;40:3187–92.Google Scholar

  • 79.

    González-Castro TB, Tovilla-Zárate C, Juárez-Rojop I, Pool García S, Genis A, Nicolini H, et al. Distribution of the Val108/158Met polymorphism of the COMT gene in healthy Mexican population. Gene 2013;526:454–8.Google Scholar

  • 80.

    Martínez-Ramírez OC, Pérez-Morales R, Castro C, Flores-Díaz A, Soto-Cruz KE, Astorga-Ramos A, et al. Polymorphisms of catechol estrogens metabolism pathway genes and breast cancer risk in Mexican women. Breast 2013;22:335–43.Google Scholar

  • 81.

    Middleton D, Williams F, Meenagh A, Daar AS, Gorodezky C, Hammond M, et al. Analysis of the distribution of HLA-A alleles in populations from five continents. Hum Immunol 2000;61:1048–52. Google Scholar

  • 82.

    Leal CA, Mendoza-Carrera F, Rivas F, Rodriguez-Reynoso S, Portilla-de Buen E. HLA-A and HLA-B allele frequencies in a mestizo population from Guadalajara, Mexico, determined by sequence-based typing. Tissue Antigens 2005;66:666–73. Google Scholar

  • 83.

    Fricke-Galindo I, Martínez-Juárez IE, Monroy-Jaramillo N, Jung-Cook H, Falfán-Valencia R, Ortega-Vázquez A, et al. HLA-A*02:01:01/-B*35:01:01/-C*04:01:01 haplotype associated with lamotrigine-induced maculopapular exanthema in Mexican Mestizo patients. Pharmacogenomics 2014;15:1881–91. Google Scholar

  • 84.

    Vargas-Alarcón G, Hernández-Pacheco G, Zuñiga J, Rodríguez-Pérez JM, Pérez-Hernández N, Rangel C, et al. Distribution of HLA-B alleles in Mexican Amerindian populations. Immunogenetics 2003;54:756–60. Google Scholar

  • 85.

    Arnaiz-Villena A, Vargas-Alarcón G, Granados J, Gómez-Casado E, Longas J, Gonzales-Hevilla M, et al. HLA genes in Mexican Mazatecans, the peopling of the Americas and the uniqueness of Amerindians. Tissue Antigens 2000;56:405–16. Google Scholar

  • 86.

    Hollenbach JA, Thomson G, Cao K, Fernandez-Vina M, Erlich HA, Bugawan TL, et al. HLA diversity, differentiation, and haplotype evolution in Mesoamerican Natives. Hum Immunol 2001;62:378–90. Google Scholar

  • 87.

    García-Ortiz JE, Sandoval-Ramírez L, Rangel-Villalobos H, Maldonado-Torres H, Cox S, García-Sepúlveda CA, et al. High-resolution molecular characterization of the HLA class I and class II in the Tarahumara Amerindian population. Tissue Antigens 2006;68:135–46. Google Scholar

  • 88.

    Leal-Ugarte E, Gutiérrez-Angulo M, Macías-Gómez NM, Peralta-Leal V, Durán-González J, De La Luz Ayala-Madrigal M, et al. MDR1 C3435T polymorphism in Mexican children with acute lymphoblastic leukemia and in healthy individuals. Hum Biol 2008;80:449–55. Google Scholar

  • 89.

    Torres-Jasso JH, Bustos-Carpinteyro AR, Marín ME, Santiago E, Leoner C, Flores-Luna L, et al. Analysis of the polymorphisms EGFR-r521K and ERBB2-I655V in Mexican patients with gastric cancer and premalignant gastric lesions. Rev Invest Clin 2013;65:150–5. Google Scholar

  • 90.

    Zavala Hernández C, Hernández Zamora E, Martínez Murillo C, Arenas Sordo M de la L, González Orozco AE, Reyes Maldonado E. Association of resistance to activated protein with the presence of Leiden and Cambridge Factor V mutations in Mexican patients with primary thrombophilia. Cir Cir 2010;78:127–32. Google Scholar

  • 91.

    Salas-Alanis JC, Mellerio JE, Ashton GH, McGrath JA. Frequency of the CCR5 gene 32-basepair deletion in Hispanic Mexicans. Clin Exp Dermatol 1999;24:127–9. Google Scholar

  • 92.

    Valadez-González N, González-Martínez P, Lara-Perera D, Vera-Gamboa L, Góngora-Biachi R. CCR5-Δ32 allele involvement in the clinical evolution of HIV1+ patients in Yucatán, Mexico. Salud Publica Mex 2011;53:463–8. Google Scholar

  • 93.

    Zúñiga JA, Villarreal-Garza C, Flores E, Barquera R, Pérez-Hernández N, Montes de Oca JV, et al. Biological relevance of the polymorphism in the CCR5 gene in refractory and non-refractory rheumatoid arthritis in Mexicans. Clin Exp Rheumatol 2003;21:351–4. Google Scholar

  • 94.

    Vaca G, Arámbula E, Esparza A. Molecular heterogeneity of glucose-6-phosphate dehydrogenase deficiency in Mexico: overall results of a 7-year project. Blood Cells Mol Dis 2002;28:436–44. Google Scholar

  • 95.

    Arámbula E, Aguilar L J, Vaca G. Glucose-6-phosphate dehydrogenase mutations and haplotypes in Mexican mestizos. Blood Cells Mol Dis 2000;26:387–94. Google Scholar

  • 96.

    García-Magallanes N, Luque-Ortega F, Aguilar-Medina EM, Ramos-Payán R, Galaviz-Hernández C, Romero-Quintana JG, et al. Glucose-6-phosphate dehydrogenase deficiency in northern Mexico and description of a novel mutation. J Genet 2014;93:325–30. Google Scholar

  • 97.

    Zamorano-Jiménez CA, Baptista-González HA, Bouchan-Valencia P, Granados-Cepeda ML, Trueba-Gómez R, Coeto-Barona G, et al. Identificación molecular de la glucosa-6-fosfato deshidrogenasa (G6PD) detectada en el tamiz neonatal. Gac Med Mex 2015;151:34–41. Google Scholar

  • 98.

    Lares-Asseff I, Sosa-Macías M, Elizondo-Azuela G, Flores-Pérez C, Flores-Pérez J, Bradley-Alvarez F. Phenotypical expression of CYP2D6 in Amerindians of Tepehuano origin from Durango, Mexico. Proc West Pharmacol Soc 2005;48:102–7. Google Scholar

  • 99.

    Gonzalez HM, Romero EM, Peregrina AA, de J Chávez T, Escobar-Islas E, Lozano F, et al. CYP2C19- and CYP3A4-dependent omeprazole metabolism in West Mexicans. J Clin Pharmacol 2003;43:1211–5. Google Scholar

  • 100.

    Atlas de los Pueblos Indígenas de México [Internet]. [cited 2015 Jul 13]. Available from: http://www.cdi.gob.mx/index.php?option=com_wrapper&view=wrapper&Itemid=200027

  • 101.

    Dean L. Tamoxifen therapy and CYP2D6 genotype [Internet]. National Center for Biotechnology Information (US); 2014 [cited 2015 Jul 14]. Available from: http://www.ncbi.nlm.nih.gov/books/NBK247013/

  • 102.

    Crews KR, Gaedigk A, Dunnenberger HM, Leeder JS, Klein TE, Caudle KE, et al. Clinical pharmacogenetics implementation consortium guidelines for cytochrome P450 2D6 genotype and codeine therapy: 2014 update. Clin Pharmacol Ther 2014;95:376–82. Google Scholar

  • 103.

    Eissing T, Lippert J, Willmann S. Pharmacogenomics of codeine, morphine, and morphine-6-glucuronide: model-based analysis of the influence of CYP2D6 activity, UGT2B7 activity, renal impairment, and CYP3A4 inhibition. Mol Diagn Ther 2012;16:43–53. Google Scholar

  • 104.

    LLerena A, Dorado P, O’Kirwan F, Jepson R, Licinio J, Wong M-L. Lower frequency of CYP2C9*2 in Mexican-Americans compared to Spaniards. Pharmacogenomics J 2004;4:403–6. Google Scholar

  • 105.

    Sangkuhl K, Klein TE, Altman RB. Clopidogrel pathway. Pharmacogenet Genomics 2010;20:463–5. Google Scholar

  • 106.

    Product information for Plavix 75 mg film-coated tablets [Internet]. [cited 2015 Jul 14]. Available from: http://www.ema.europa.eu/docs/en_GB/document_library/EPAR_-_Product_Information/human/000174/WC500042189.pdf

  • 107.

    Label information for Plavix (clopidogrel bisulfate) tablets [Internet]. [cited 2015 Jul 14]. Available from: http://www.accessdata.fda.gov/drugsatfda_docs/label/2013/020839s058lbl.pdf

  • 108.

    Kinzig-Schippers M, Tomalik-Scharte D, Jetter A, Scheidel B, Jakob V, Rodamer M, et al. Should we use N-acetyltransferase type 2 genotyping to personalize isoniazid doses? Antimicrob Agents Chemother 2005;49:1733–8. Google Scholar

  • 109.

    Mutchinick OM, López MA, Luna L, Waxman J, Babinsky VE. High prevalence of the thermolabile methylenetetrahydrofolate reductase variant in Mexico: a country with a very high prevalence of neural tube defects. Mol Genet Metab 1999;68:461–7. Google Scholar

  • 110.

    Wilcken B, Bamforth F, Li Z, Zhu H, Ritvanen A, Renlund M, et al. Geographical and ethnic variation of the 677C>T allele of 5,10 methylenetetrahydrofolate reductase (MTHFR): findings from over 7000 newborns from 16 areas world wide. J Med Genet 2003;40:619–25. Google Scholar

  • 111.

    Bradford K, Shih DQ. Optimizing 6-mercaptopurine and azathioprine therapy in the management of inflammatory bowel disease. World J Gastroenterol 2011;17:4166–73. Google Scholar

  • 112.

    Highlights of prescribing information. Purixan (mercaptopurine) oral suspension [Internet]. 2014 [cited 2015 Jul 14]. Available from: http://www.accessdata.fda.gov/drugsatfda_docs/label/2014/205919s000lbl.pdf

  • 113.

    Product information for Xaluprine 20 mg/ml oral suspension [Internet]. [cited 2015 Jul 14]. Available from: http://www.ema.europa.eu/docs/en_GB/document_library/EPAR_-_Product_Information/human/002022/WC500124645.pdf

  • 114.

    Innocenti F, Vokes EE, Ratain MJ. Irinogenetics: what is the right star? J Clin Oncol 2006;24:2221–4. Google Scholar

  • 115.

    Mathijssen RH, Marsh S, Karlsson MO, Xie R, Baker SD, Verweij J, et al. Irinotecan pathway genotype analysis to predict pharmacokinetics. Clin Cancer Res 2003;9:3246–53. Google Scholar

  • 116.

    FDA. Literature Review Update. Camptosar. Irinotecan hydrochloride injection [Internet]. 2006. [cited 2015 Jul 14]. Available from: http://www.accessdata.fda.gov/drugsatfda_docs/label/2006/020571s030lbl.pdf

  • 117.

    Etienne-Grimaldi M-C, Boyer J-C, Thomas F, Quaranta S, Picard N, Loriot M-A, et al. UGT1A1 genotype and irinotecan therapy: general review and implementation in routine practice. Fundam Clin Pharmacol 2015;29:219–37. Google Scholar

  • 118.

    Gage BF, Lesko LJ. Pharmacogenetics of warfarin: regulatory, scientific, and clinical issues. J Thromb Thrombolysis 2008;25:45–51. Google Scholar

  • 119.

    Johnson JA, Gong L, Whirl-Carrillo M, Gage BF, Scott SA, Stein CM, et al. Clinical pharmacogenetics implementation consortium guidelines for CYP2C9 and VKORC1 genotypes and warfarin dosing. Clin Pharmacol Ther 2011;90: 625–9. Google Scholar

Supplemental Material:

The online version of this article (DOI: 10.1515/dmpt-2015-0030) offers supplementary material, available to authorized users.

About the article

Corresponding author: Marisol López-López, Biological Systems Department, Universidad Autónoma Metropolitana, Campus Xochimilco, Calzada del Hueso 1100, Col. Villa Quietud, Coyoacán, Mexico City 04960, Mexico, Phone: +52-55-5483-7250, Fax: +52-55-5483-7237, E-mail:

Received: 2015-08-24

Accepted: 2015-12-04

Published Online: 2016-01-14

Published in Print: 2016-06-01

Citation Information: Drug Metabolism and Personalized Therapy, Volume 31, Issue 2, Pages 61–81, ISSN (Online) 2363-8915, ISSN (Print) 2363-8907, DOI: https://doi.org/10.1515/dmpt-2015-0030.

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