Genetic diversity of HLA system in six populations from Mexico City Metropolitan Area, Mexico: Mexico City North, Mexico City South, Mexico City East, Mexico City West, Mexico City Center and rural Mexico City

Barquera, Rodrigo; Martínez-Álvarez, Julio César; Hernández-Zaragoza, Diana Iraíz; Bravo-Acevedo, Alicia; Juárez-Nicolás, Francisco; Arriaga-Perea, Agustín Jericó; Vega-Martínez, María del Rosario; Ortega-Yáñez, Andrea; Benítez-Arvizu, Gamaliel; Arrieta-Bolaños, Esteban; Clayton, Stephen; Juárez-Cortés, Eva Dolores; López-Gil, Concepción; García-Álvarez, Raquel; Arrazola-García, María Araceli; Martínez-Bezies, Virginia; Juárez-Barreto, Vicencio; Cruz, Flor del Rocío Ramos-de la; Macías-Medrano, Rosa María; Méndez-Mani, Patricia; Escutia-González, Ariadna Berenice; Montiel-Hernández, Gustavo Daniel; Immel, Alexander; Pavón-Vargas, María de los Ángeles; Salgado-Galicia, Norma; Novelo-Garza, Bárbara; Zúñiga, Joaquı́n; Yunis, Edmond J.; Bekker-Méndez, Carolina; Granados, Julio

doi:10.1016/j.humimm.2019.07.297

Cited by 4 publications

(6 citation statements)

References 20 publications

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“…Mexico City, considered part of Central Mexico, has higher Amerindian ancestry than northern and western Mexico, [25]. In agreement with previous studies, on average, more than half of Mexican ancestry from Central Mexicans is Amerindian (mean AMA = 57% in this study) [26,27]. Ancestry differences could be explained, at least in part, by differences in genetic markers predisposing high childhood BMI and %BF values between Mexican and European children.…”

Section: Discussionsupporting

confidence: 91%

Genome-Wide Association Study of Body Mass Index and Body Fat in Mexican-Mestizo Children

Costa-Urrutia

Colistro

Jiménez-Osorio

et al. 2019

Genes

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Background: Childhood obesity is a major health problem in Mexico. Obesity prevalence estimated by body mass index (BMI) is almost half than that estimated by percent body fat (%BF) in the Childhood Obesity pediatric cohort (COIPIS). Objective. We performed a genome-wide association study (GWAS) of BMI and %BF in 828 children from the COIPIS to identify markers of predisposition to high values for both phenotypes used for obesity classification. Methods: For the GWAS we used the LAT Axiom 1, Affymetrix and 2.5 million single loci from the 1000 Genomes Phase 3 imputation panel. We used a linear model, adjusted by age, sex, and Amerindian ancestry assuming an additive inheritance model. Results. Genome-wide significance (p ≤ 5.0 × 10−8) and 80% of statistical power was reached for associations of two loci in two genes (CERS3 and CYP2E1) to BMI. Also, 11 loci in six genes (ANKS1B, ARNTL2, KCNS3, LMNB1, SRGAP3, TRPC7) reached genome-wide significance for associations to %BF, though not 80% of statistical power. Discussion: None of the SNPs were previously reported as being associated to BMI or %BF. In addition, different loci were found for BMI and %BF. These results highlight the importance of gaining deeper understanding of genetic markers of predisposition to high values for the phenotypes used for obesity diagnosis.

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Section: Discussionsupporting

confidence: 91%

Genome-Wide Association Study of Body Mass Index and Body Fat in Mexican-Mestizo Children

Costa-Urrutia

Colistro

Jiménez-Osorio

et al. 2019

Genes

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“…In this study were studied 1217 individuals northern (N = 751), southern (N = 52), eastern (N = 79), western (N = 33), and central (N = 152) Mexico City and surroundings. Admixture estimates are very similar to the calculations performed by Maximum likelihood in our study, being Native American Mexican 63.85%, European 28.53%, and African 7.61% (Barquera et al, 2020e).…”

Section: Discussionsupporting

confidence: 86%

“…Mexican Mestizo populations from Northern Mexico (7 populations): Baja California ( Escobedo-Ruíz et al, 2020 ), Chihuahua ( Pacheco-Ubaldo et al, 2020 ), Colima ( Barquera et al, 2020b ), Durango ( González-Medina et al, 2020 ), Nuevo León ( Barquera et al, 2020a ), Sinaloa ( Clayton et al, 2020 ), and Sonora ( Uribe-Duarte et al, 2020 ). Mexican Mestizo populations from the Center of Mexico (14 populations): Aguascalientes ( Bravo-Acevedo et al, 2020 ), Guanajuato ( Pantoja-Torres et al, 2020 ), Guerrero ( Juárez-Nicolás et al, 2020 ), Jalisco ( Bravo-Acevedo et al, 2020 ), Mexico City Center, Mexico City Western, Mexico City Eastern, Mexico City Southern, Mexico City Northern ( Barquera et al, 2020e ), Michoacán ( Ballesteros-Romero et al, 2020 ), Morelos ( Ortega-Yáñez et al, 2020 ), Nayarit ( Goné-Vázquez et al, 2020 ), Querétaro ( Martínez-Álvarez et al, 2020 ), and San Luis Potosí ( Hernández-Zaragoza et al, 2020 ). Mexican Mestizo populations from Southern Mexico (4 populations): Chiapas ( Barquera et al, 2020d ), Oaxaca ( Hernández-Hernández et al, 2020 ), Quintana Roo ( Medina-Escobedo et al, 2020 ) and Tabasco ( Solís-Martínez et al, 2020 ).…”

Section: Subjects Materials and Methodsmentioning

confidence: 99%

“…Otherwise, HLA-DR2 Chiapas patients showed a higher risk of developing SLE once infected with Zika or Chikungunya viruses common in that region but absent in Mexico City ( Sepúlveda Delgado et al, 2018 ). Besides, population genetic studies revealed significantly different admixture estimates for Mexico City and Tapachula, Chiapas ( Barquera et al, 2020e ).…”

Section: Introductionmentioning

confidence: 99%

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Heterogeneity of Genetic Admixture Determines SLE Susceptibility in Mexican

et al. 2021

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Systemic Lupus Erythematosus (SLE) is an autoimmune inflammatory disorder for which Major Histocompatibility Complex (MHC) genes are well identified as risk factors. SLE patients present different clinical phenotypes, which are partly explained by admixture patterns variation among Mexicans. Population genetic has insight into the high genetic variability of Mexicans, mainly described through HLA gene studies with anthropological and biomedical importance. A prospective, case-control study was performed. In this study, we recruited 146 SLE patients, and 234 healthy individuals were included as a control group; both groups were admixed Mexicans from Mexico City. The HLA typing methods were based on Next Generation Sequencing and Sequence-Based Typing (SBT). The data analysis was performed with population genetic programs and statistical packages. The admixture estimations based on HLA-B and -DRB1 revealed that SLE patients have a higher Southwestern European ancestry proportion (48 ± 8%) than healthy individuals (30 ± 7%). In contrast, Mexican Native American components are diminished in SLE patients (44 ± 1%) and augmented in Healthy individuals (63 ± 4%). HLA alleles and haplotypes’ frequency analysis found variants previously described in SLE patients from Mexico City. Moreover, a conserved extended haplotype that confers risk to develop SLE was found, the HLA-A∗29:02∼C∗16:01∼B∗44:03∼DRB1∗07:01∼DQB1∗02:02, pC = 0.02, OR = 1.41. Consistent with the admixture estimations, the origin of all risk alleles and haplotypes found in this study are European, while the protection alleles are Mexican Native American. The analysis of genetic distances supported that the SLE patient group is closer to the Southwestern European parental populace and farthest from Mexican Native Americans than healthy individuals. Heterogeneity of genetic admixture determines SLE susceptibility and protection in Mexicans. HLA sequencing is helpful to determine susceptibility alleles and haplotypes restricted to some populations.

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“…On the other hand, up to now, Mexico City is the region with the highest number of reported cases. The studies regarding allele frequency in this city have reported that its haplotype is largely composed of Native American haplotypes, specifically 63.85 ± 1.55% American, 28.53 ± 3.13% European, and a less apparent 7.61 ± 1.96% African 17 . Individually, some studies have reported that the most frequent alleles in Mexican population are HLA‐A*02, ‐A*24, ‐A*68, ‐B*35, ‐B*39, ‐B*51, ‐DRB1*04, ‐DRB1*08, ‐DRB1*07, ‐DQB1*0302, ‐DQB1*0301, and ‐DQB1*0201 18 .…”

Section: Introductionmentioning

confidence: 90%

A bioinformatic prediction of antigen presentation from SARS‐CoV‐2 spike protein revealed a theoretical correlation of HLA‐DRB1*01 with COVID‐19 fatality in Mexican population: An ecological approach

Romero-López

Carnalla

Pacheco-Olvera

et al. 2020

Journal of Medical Virology

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SARS‐CoV‐2 infection is causing a pandemic disease that is reflected in challenging public health problems worldwide. HLA‐based epitope prediction and its association with disease outcomes provide an important base for treatment design. A bioinformatic prediction of T cell epitopes and their restricted HLA class I and II alleles was performed to obtain immunogenic epitopes and HLA alleles from the spike protein of the SARS‐CoV‐2 virus. Also, a correlation with the predicted fatality rate of hospitalized patients in 28 states of Mexico was done. Here, we describe a set of ten highly immunogenic epitopes, together with different HLA alleles that can efficiently present these epitopes to T cells. Most of these epitopes are located within the S1 subunit of the spike protein, suggesting that this area is highly immunogenic. A statistical negative correlation was found between the frequency of HLA‐DRB1*01 and the fatality rate in hospitalized patients in Mexico. This article is protected by copyright. All rights reserved.

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Genetic diversity of HLA system in six populations from Mexico City Metropolitan Area, Mexico: Mexico City North, Mexico City South, Mexico City East, Mexico City West, Mexico City Center and rural Mexico City

Cited by 4 publications

References 20 publications

Genome-Wide Association Study of Body Mass Index and Body Fat in Mexican-Mestizo Children

Genome-Wide Association Study of Body Mass Index and Body Fat in Mexican-Mestizo Children

Heterogeneity of Genetic Admixture Determines SLE Susceptibility in Mexican

A bioinformatic prediction of antigen presentation from SARS‐CoV‐2 spike protein revealed a theoretical correlation of HLA‐DRB1*01 with COVID‐19 fatality in Mexican population: An ecological approach

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