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Your search keyword '"Vazquez, Lyam"' showing total 2 results
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2 results on '"Vazquez, Lyam"'

1. The impact of the metabotropic glutamate receptor and other gene family interaction networks on autism.

Author

Hadley, Dexter, Wu, Zhi-Liang, Kao, Charlly, Kini, Akshata, Mohamed-Hadley, Alisha, Thomas, Kelly, Vazquez, Lyam, Qiu, Haijun, Mentch, Frank, Pellegrino, Renata, Kim, Cecilia, Connolly, John, AGP Consortium, Glessner, Joseph, and Hakonarson, Hakon

Subjects
AGP Consortium, Humans, Calmodulin, Proto-Oncogene Proteins c-myc, Receptors, Metabotropic Glutamate, Autistic Disorder, Child, Child, Preschool, Female, Male, Basic Helix-Loop-Helix Leucine Zipper Transcription Factors, Gene Regulatory Networks, DNA Copy Number Variations, Receptors, Metabotropic Glutamate, Preschool
Abstract

Although multiple reports show that defective genetic networks underlie the aetiology of autism, few have translated into pharmacotherapeutic opportunities. Since drugs compete with endogenous small molecules for protein binding, many successful drugs target large gene families with multiple drug binding sites. Here we search for defective gene family interaction networks (GFINs) in 6,742 patients with the ASDs relative to 12,544 neurologically normal controls, to find potentially druggable genetic targets. We find significant enrichment of structural defects (P ≤ 2.40E-09, 1.8-fold enrichment) in the metabotropic glutamate receptor (GRM) GFIN, previously observed to impact attention deficit hyperactivity disorder (ADHD) and schizophrenia. Also, the MXD-MYC-MAX network of genes, previously implicated in cancer, is significantly enriched (P ≤ 3.83E-23, 2.5-fold enrichment), as is the calmodulin 1 (CALM1) gene interaction network (P ≤ 4.16E-04, 14.4-fold enrichment), which regulates voltage-independent calcium-activated action potentials at the neuronal synapse. We find that multiple defective gene family interactions underlie autism, presenting new translational opportunities to explore for therapeutic interventions.

Published
2014

2. Leveraging Electronic Health Records to Assess the Role of ADRB2 SNPs in Predicting Exacerbation Frequency in Asthma Patients

Author

Sood, Nikita, Connolly, John J, Mentch, Frank, Vazquez, Lyam, Hysinger, Erik, and Hakonarson, Hakon

Subjects
Adult, Male, Heterozygote, Adolescent, Genotype, Polymorphism, Single Nucleotide, Article, Asthma, Young Adult, Gene Frequency, Adrenal Cortex Hormones, Pharmacogenetics, Electronic Health Records, Humans, Female, Genetic Predisposition to Disease, Receptors, Adrenergic, beta-2, Child, Alleles
Abstract

Asthma is the leading chronic disease in children. Several studies have identified genetic biomarkers associated with susceptibility and severity in both adult and pediatric cases. In this study, we evaluated outcomes in 400 African American and European American pediatric cases all of whom were regular users of inhaled corticosteroids. Patients were stratified by genotype using two single nucleotide polymorphisms in the β-2-adrenergic receptor (ADRB2) gene - rs1042713 and rs1042714, previously associated with asthma outcome. These correspond to nonsynonymous single nucleotide polymorphisms at positions 16 [arginine to glycine (Arg16Gly); rs1042713] and 27 [glutamic acid to glutamine (Glu27Gln); rs1042714], which are relatively common (minor allele frequencies ∼40-50%), and have been well characterized in asthma pharmacogenetics. We controlled for adherence to the National Heart, Lung and Blood Institute guidelines using deep mining of electronic health record data to determine treatment course. We found no significant effect for rs1042713 (Arg16Gly) but did identify an effect for rs1042714, where participants homozygous for Gln27 had increased exacerbations while taking inhaled corticosteroids in comparison with those who were either heterozygous or homozygous for Glu27. This is consistent with previous studies and demonstrates for the first time that the Glu27 variant in the ADRB2 gene is associated with increased frequencies of asthma exacerbations. Moreover, this study also lends an important proof-of-principle on how electronic health records linked to genotype can be efficiently and systematically mined to delineate health outcomes.

Published
2018

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