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1.
Proc Natl Acad Sci U S A ; 106(21): 8611-6, 2009 May 26.
Article in English | MEDLINE | ID: mdl-19433783

ABSTRACT

Mexico is developing the basis for genomic medicine to improve healthcare of its population. The extensive study of genetic diversity and linkage disequilibrium structure of different populations has made it possible to develop tagging and imputation strategies to comprehensively analyze common genetic variation in association studies of complex diseases. We assessed the benefit of a Mexican haplotype map to improve identification of genes related to common diseases in the Mexican population. We evaluated genetic diversity, linkage disequilibrium patterns, and extent of haplotype sharing using genomewide data from Mexican Mestizos from regions with different histories of admixture and particular population dynamics. Ancestry was evaluated by including 1 Mexican Amerindian group and data from the HapMap. Our results provide evidence of genetic differences between Mexican subpopulations that should be considered in the design and analysis of association studies of complex diseases. In addition, these results support the notion that a haplotype map of the Mexican Mestizo population can reduce the number of tag SNPs required to characterize common genetic variation in this population. This is one of the first genomewide genotyping efforts of a recently admixed population in Latin America.


Subject(s)
Genetic Variation/genetics , Genome, Human/genetics , Genomics , Indians, North American/genetics , Medicine , Alleles , Haplotypes , Humans , Mexico
2.
Bioinformatics ; 23(13): i167-74, 2007 Jul 01.
Article in English | MEDLINE | ID: mdl-17646293

ABSTRACT

MOTIVATION: The identification of risk-associated genetic variants in common diseases remains a challenge to the biomedical research community. It has been suggested that common statistical approaches that exclusively measure main effects are often unable to detect interactions between some of these variants. Detecting and interpreting interactions is a challenging open problem from the statistical and computational perspectives. Methods in computing science may improve our understanding on the mechanisms of genetic disease by detecting interactions even in the presence of very low heritabilities. RESULTS: We have implemented a method using Genetic Programming that is able to induce a Decision Tree to detect interactions in genetic variants. This method has a cross-validation strategy for estimating classification and prediction errors and tests for consistencies in the results. To have better estimates, a new consistency measure that takes into account interactions and can be used in a genetic programming environment is proposed. This method detected five different interaction models with heritabilities as low as 0.008 and with prediction errors similar to the generated errors. AVAILABILITY: Information on the generated data sets and executable code is available upon request.


Subject(s)
Algorithms , Chromosome Mapping/methods , Decision Support Techniques , Epistasis, Genetic , Genetic Predisposition to Disease/genetics , Genetics, Population , Models, Genetic , Animals , Genetic Testing/methods , Humans , Penetrance
3.
Eur J Hum Genet ; 15(3): 336-41, 2007 Mar.
Article in English | MEDLINE | ID: mdl-17228327

ABSTRACT

A regulatory single nucleotide polymorphism (SNP) PD1.3G/A located on programmed cell death 1 (PDCD1) gene, was shown to be involved in susceptibility to systemic lupus erythematosus (SLE) in Swedish, European American, and Mexican cases. However, association to childhood-onset SLE has not been analyzed. The aim of this study was to investigate the association of PDCD1 polymorphisms and haplotypes with susceptibility to childhood-onset SLE in Mexican population. Three PDCD1 SNPs, PD1.3G/A, PD1.5C/T, PD1.6G/A, were analyzed in 250 childhood-onset SLE Mexican patients and 355 healthy controls in a case-control association study. Polymorphisms were genotyped by TaqMan technology. Stratification analysis was performed on the SLE cohort to investigate the SNP association with renal disorder. In addition, haplotypes were constructed with these three SNPs. The PD1.3A allele was significantly associated to childhood-onset SLE (P=0.0019, odds ratio (OR) 2.73, 95% confidence interval (95% CI) 1.35-5.56). The other PDCD1 SNPs did not show association. A total of 155 patients (62%) had nephritis, and no association was observed with PDCD1 SNPs. The ACG haplotype (PD1.3A, PD1.5C, PD1.6G) included almost all PD1.3A alleles, and it was more frequent in SLE patients (5.5%) than in controls (2.1%) (P=0.003; OR 2.73, 95% CI 1.37-5.46). The haplotype structure in Mexican controls was significantly different from those reported in Spanish and Swedish. Our results support association of the PD1.3A SNP to susceptibility of childhood-onset SLE in Mexican population and does not show association to lupus nephritis in this age group.


Subject(s)
Antigens, CD/genetics , Apoptosis Regulatory Proteins/genetics , Genetic Predisposition to Disease , Lupus Erythematosus, Systemic/genetics , Polymorphism, Genetic , Age of Onset , Case-Control Studies , Child , Female , Humans , Lupus Erythematosus, Systemic/epidemiology , Lupus Nephritis/genetics , Male , Programmed Cell Death 1 Receptor
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