Genetics of sputum gene expression in chronic obstructive pulmonary disease

Previous expression quantitative trait loci (eQTL) studies have performed genetic association studies for gene expression, but most of these studies examined lymphoblastoid cell lines from non-diseased individuals. We examined the genetics of gene expression in a relevant disease tissue from chronic obstructive pulmonary disease (COPD) patients to identify functional effects of known susceptibility genes and to find novel disease genes. By combining gene expression profiling on induced sputum samples from 131 COPD cases from the ECLIPSE Study with genomewide single nucleotide polymorphism (SNP) data, we found 4315 significant cis-eQTL SNP-probe set associations (3309 unique SNPs). The 3309 SNPs were tested for association with COPD in a genomewide association study (GWAS) dataset, which included 2940 COPD cases and 1380 controls. Adjusting for 3309 tests (p<1.5e-5), the two SNPs which were significantly associated with COPD were located in two separate genes in a known COPD locus on chromosome 15: CHRNA5 and IREB2. Detailed analysis of chromosome 15 demonstrated additional eQTLs for IREB2 mapping to that gene. eQTL SNPs for CHRNA5 mapped to multiple linkage disequilibrium (LD) bins. The eQTLs for IREB2 and CHRNA5 were not in LD. Seventy-four additional eQTL SNPs were associated with COPD at p<0.01. These were genotyped in two COPD populations, finding replicated associations with a SNP in PSORS1C1, in the HLA-C region on chromosome 6. Integrative analysis of GWAS and gene expression data from relevant tissue from diseased subjects has located potential functional variants in two known COPD genes and has identified a novel COPD susceptibility locus.     

SNP-based large-scale identification of allele-specific gene expression in human B cells

Polymorphism and variations in gene expression provide the genetic basis for human variation. Allelic variation of gene expression, in particular, may play a crucial role in phenotypic variation and disease susceptibility. To identify genes with allelic expression in human cells, we genotyped genomic DNA and cDNA isolated from 31 immortalized B cell lines from three Centre d'Etude du Polymorphisme Humain (CEPH) families using high-density single-nucleotide polymorphism (SNP) chips containing 13,900 exonic SNPs. We identified seven SNPs in five genes with monoallelic expression, 146 SNPs in 125 genes with allelic imbalance in expression with preferentially higher expression of one allele in a heterozygous individual. The monoallelically expressed genes (ERAP2, MDGA1, LOC644422, SDCCAG3P1 and CLTCL1) were regulated by cis-acting, non-imprinted differential allelic control. In addition, all monoallelic gene expression patterns and allelic imbalances in gene expression in B cells were transmitted from parents to offspring in the pedigree, indicating genetic transmission of allelic gene expression. Furthermore, frequent allele substitution, probably due to RNA editing, was also observed in 21 genes in 23 SNPs as well as in 48 SNPs located in regions containing no known genes. In this study, we demonstrated that allelic gene expression is frequently observed in human B cells, and SNP chips are very useful tools for detecting allelic gene expression. Overall, our data provide a valuable framework for better understanding allelic gene expression in human B cells.     

Prevalent function of genome loci associated with development of multiple sclerosis as revealed by GWAS and eQTL analysis

We studied genome distribution of single-nucleotide polymorphisms (SNP) associated with development of multiple sclerosis and identified genome segments enriched in such polymorphisms. Some SNPs observed in identified segments are also local or distal eQTLs (expression quantitative trait loci) for a number of genes expressed in the blood or the nervous system. We analyzed lists of genes expression of which depends on these eQTLs, separately for the blood and the nervous system, and identified GO functions overrepresented in such gene lists. An antigen processing and presentation via MHC class II appeared to be the main gene functions either in the blood or in the nervous system. We identified a set of SNPs genetically linked with at least three SNPs associated with multiple sclerosis in GWAS, which includes eQTLs for all overrepresented functions. These SNPs and genes are located in a rather short locus on chromosome 14 presumably containing IGHG genes. SNPs from this genome segment affect expression of the HLA-DOB, HLA-DQA1, HLA-DQA2, and HLA-DQB1 genes both in the blood and in the nervous system. The results we obtained made it possible to suggest the mechanisms of multiple sclerosis development.     

Atrial Fibrillation Associated Chromosome 4q25 Variants Are Not Associated with PITX2c Expression in Human Adult Left Atrial Appendages

Atrial Fibrillation (AF), the most common sustained arrhythmia, has a strong genetic component, but the mechanism by which common genetic variants lead to increased AF susceptibility is unknown. Genome-wide association studies (GWAS) have identified that the single nucleotide polymorphisms (SNPs) most strongly associated with AF are located on chromosome 4q25 in an intergenic region distal to the PITX2 gene. Our objective was to determine whether the AF-associated SNPs on chromosome 4q25 were associated with PITX2c expression in adult human left atrial appendages. Analysis of a lone AF GWAS identified four independent AF risk SNPs at chromosome 4q25. Human adult left atrial appendage tissue was obtained from 239 subjects of European Ancestry and used for SNP analysis of genomic DNA and determination of PITX2c RNA expression levels by quantitative PCR. Subjects were divided into three groups based on their history of AF and pre-operative rhythm. AF rhythm subjects had higher PITX2c expression than those with history of AF but in sinus rhythm. PITX2c expression was not associated with the AF risk SNPs in human adult left atrial appendages in all subjects combined or in each of the three subgroups. However, we identified seven SNPs modestly associated with PITX2c expression located in the introns of the ENPEP gene, ∼54 kb proximal to PITX2. PITX2c expression in human adult left atrial appendages is not associated with the chromosome 4q25 AF risk SNPs; thus, the mechanism by which these SNPs are associated with AF remains enigmatic.     

Genome-wide Association Study Reveals Multiple Nasopharyngeal Carcinoma-Associated Loci within the HLA Region at Chromosome 6p21.3

Nasopharyngeal carcinoma (NPC) is a multifactorial malignancy closely associated with genetic factors and Epstein-Barr virus infection. To identify the common genetic variants linked to NPC susceptibility, we conducted a genome-wide association study (GWAS) in 277 NPC patients and 285 healthy controls within the Taiwanese population, analyzing 480,365 single-nucleotide polymorphisms (SNPs). Twelve statistically significant SNPs were identified and mapped to chromosome 6p21.3. Associations were replicated in two independent sets of case-control samples. Two of the most significant SNPs (rs2517713 and rs2975042; p_combined = 3.9 × 10⁻²⁰ and 1.6 × 10⁻¹⁹, respectively) were located in the HLA-A gene. Moreover, we detected significant associations between NPC and two genes: specifically, gamma aminobutyric acid b receptor 1 (GABBR1) (rs29232; p_combined = 8.97 × 10⁻¹⁷) and HLA-F (rs3129055 and rs9258122; p_combined = 7.36 × 10⁻¹¹ and 3.33 × 10⁻¹⁰, respectively). Notably, the association of rs29232 remained significant (residual p < 5 × 10⁻⁴) after adjustment for age, gender, and HLA-related SNPs. Furthermore, higher GABA_B receptor 1 expression levels can be found in the tumor cells in comparison to the adjacent epithelial cells (p < 0.001) in NPC biopsies, implying a biological role of GABBR1 in NPC carcinogenesis. To our knowledge, it is the first GWAS report of NPC showing that multiple loci (HLA-A, HLA-F, and GABBR1) within chromosome 6p21.3 are associated with NPC. Although some of these relationships may be attributed to linkage disequilibrium between the loci, the findings clearly provide a fresh direction for the study of NPC development.     

Comparison of Genomic and Epigenomic Expression in Monozygotic Twins Discordant for Rett Syndrome

Monozygotic (identical) twins have been widely used in genetic studies to determine the relative contributions of heredity and the environment in human diseases. Discordance in disease manifestation between affected monozygotic twins has been attributed to either environmental factors or different patterns of X chromosome inactivation (XCI). However, recent studies have identified genetic and epigenetic differences between monozygotic twins, thereby challenging the accepted experimental model for distinguishing the effects of nature and nurture. Here, we report the genomic and epigenomic sequences in skin fibroblasts of a discordant monozygotic twin pair with Rett syndrome, an X-linked neurodevelopmental disorder characterized by autistic features, epileptic seizures, gait ataxia and stereotypical hand movements. The twins shared the same de novo mutation in exon 4 of the MECP2 gene (G269AfsX288), which was paternal in origin and occurred during spermatogenesis. The XCI patterns in the twins did not differ in lymphocytes, skin fibroblasts, and hair cells (which originate from ectoderm as does neuronal tissue). No reproducible differences were detected between the twins in single nucleotide polymorphisms (SNPs), insertion-deletion polymorphisms (indels), or copy number variations. Differences in DNA methylation between the twins were detected in fibroblasts in the upstream regions of genes involved in brain function and skeletal tissues such as Mohawk Homeobox (MKX), Brain-type Creatine Kinase (CKB), and FYN Tyrosine Kinase Protooncogene (FYN). The level of methylation in these upstream regions was inversely correlated with the level of gene expression. Thus, differences in DNA methylation patterns likely underlie the discordance in Rett phenotypes between the twins.     

Protein-Protein Interaction Analysis Highlights Additional Loci of Interest for Multiple Sclerosis

Genetic factors play an important role in determining the risk of multiple sclerosis (MS). The strongest genetic association in MS is located within the major histocompatibility complex class II region (MHC), but more than 50 MS loci of modest effect located outside the MHC have now been identified. However, the relative candidate genes that underlie these associations and their functions are largely unknown. We conducted a protein-protein interaction (PPI) analysis of gene products coded in loci recently reported to be MS associated at the genome-wide significance level and in loci suggestive of MS association. Our aim was to identify which suggestive regions are more likely to be truly associated, which genes are mostly implicated in the PPI network and their expression profile. From three recent independent association studies, SNPs were considered and divided into significant and suggestive depending on the strength of the statistical association. Using the Disease Association Protein-Protein Link Evaluator tool we found that direct interactions among genetic products were significantly higher than expected by chance when considering both significant regions alone (p<0.0002) and significant plus suggestive (p<0.007). The number of genes involved in the network was 43. Of these, 23 were located within suggestive regions and many of them directly interacted with proteins coded within significant regions. These included genes such as SYK, IL-6, CSF2RB, FCLR3, EIF4EBP2 and CHST12. Using the gene portal BioGPS, we tested the expression of these genes in 24 different tissues and found the highest values among immune-related cells as compared to non-immune tissues (p<0.001). A gene ontology analysis confirmed the immune-related functions of these genes. In conclusion, loci currently suggestive of MS association interact with and have similar expression profiles and function as those significantly associated, highlighting the fact that more common variants remain to be found to be associated to MS.     

Additive,Epistatic, and Environmental Effects Through the Lens of Expression Variability QTL in a Twin Cohort

The expression of a gene can vary across individuals in the general population, as well as between monozygotic twins. This variable expression is assumed to be due to the influence of both genetic and nongenetic factors. Yet little evidence supporting this assumption has been obtained from empirical data. In this study, we used expression data from a large twin cohort to investigate the influences of genetic and nongenetic factors on variable gene expression. We focused on a set of expression variability QTL (evQTL)—i.e., genetic loci associated with the variance, as opposed to the mean, of gene expression. We identified evQTL for 99, 56, and 79 genes in lymphoblastoid cell lines, skin, and fat, respectively. The differences in gene expression, measured by the relative mean difference (RMD), tended to be larger between pairs of dizygotic (DZ) twins than between pairs of monozygotic (MZ) twins, showing that genetic background influenced the expression variability. Furthermore, a more profound RMD was observed between pairs of MZ twins whose genotypes were associated with greater expression variability than the RMD found between pairs of MZ twins whose genotypes were associated with smaller expression variability. This suggests that nongenetic (e.g., environmental) factors contribute to the variable expression. Lastly, we demonstrated that the formation of evQTL is likely due to partial linkages between eQTL SNPs that are additively associated with the mean of gene expression; in most cases, no epistatic effect is involved. Our findings have implications for understanding divergent sources of gene expression variability.     

Batch effect correction for genome-wide methylation data with Illumina Infinium platform

Background

Paclitaxel is a microtubule-stabilizing drug that has been commonly used in treating cancer. Due to genetic heterogeneity within patient populations, therapeutic response rates often vary. Here we used the NCI60 panel to identify SNPs associated with paclitaxel sensitivity. Using the panel's GI50 response data available from Developmental Therapeutics Program, cell lines were categorized as either sensitive or resistant. PLINK software was used to perform a genome-wide association analysis of the cellular response to paclitaxel with the panel's SNP-genotype data on the Affymetrix 125 k SNP array. FastSNP software helped predict each SNP's potential impact on their gene product. mRNA expression differences between sensitive and resistant cell lines was examined using data from BioGPS. Using Haploview software, we investigated for haplotypes that were more strongly associated with the cellular response to paclitaxel. Ingenuity Pathway Analysis software helped us understand how our identified genes may alter the cellular response to paclitaxel.

Results

43 SNPs were found significantly associated (FDR < 0.005) with paclitaxel response, with 10 belonging to protein-coding genes (CFTR, ROBO1, PTPRD, BTBD12, DCT, SNTG1, SGCD, LPHN2, GRIK1, ZNF607). SNPs in GRIK1, DCT, SGCD and CFTR were predicted to be intronic enhancers, altering gene expression, while SNPs in ZNF607 and BTBD12 cause conservative missense mutations. mRNA expression analysis supported these findings as GRIK1, DCT, SNTG1, SGCD and CFTR showed significantly (p < 0.05) increased expression among sensitive cell lines. Haplotypes found in GRIK1, SGCD, ROBO1, LPHN2, and PTPRD were more strongly associated with response than their individual SNPs.

Conclusions

Our study has taken advantage of available genotypic data and its integration with drug response data obtained from the NCI60 panel. We identified 10 SNPs located within protein-coding genes that were not previously shown to be associated with paclitaxel response. As only five genes showed differential mRNA expression, the remainder would not have been detected solely based on expression data. The identified haplotypes highlight the role of utilizing SNP combinations within genomic loci of interest to improve the risk determination associated with drug response. These genetic variants represent promising biomarkers for predicting paclitaxel response and may play a significant role in the cellular response to paclitaxel.     

A Genome-Wide Association Study Suggests Novel Loci Associated with a Schizophrenia-Related Brain-Based Phenotype

Patients with schizophrenia and their siblings typically show subtle changes of brain structures, such as a reduction of hippocampal volume. Hippocampal volume is heritable, may explain a variety of cognitive symptoms of schizophrenia and is thus considered an intermediate phenotype for this mental illness. The aim of our analyses was to identify single-nucleotide polymorphisms (SNP) related to hippocampal volume without making prior assumptions about possible candidate genes. In this study, we combined genetics, imaging and neuropsychological data obtained from the Mind Clinical Imaging Consortium study of schizophrenia (n = 328). A total of 743,591 SNPs were tested for association with hippocampal volume in a genome-wide association study. Gene expression profiles of human hippocampal tissue were investigated for gene regions of significantly associated SNPs. None of the genetic markers reached genome-wide significance. However, six highly correlated SNPs (rs4808611, rs35686037, rs12982178, rs1042178, rs10406920, rs8170) on chromosome 19p13.11, located within or in close proximity to the genes NR2F6, USHBP1, and BABAM1, as well as four SNPs in three other genomic regions (chromosome 1, 2 and 10) had p-values between 6.75×10⁻⁶ and 8.3×10⁻⁷. Using existing data of a very recently published GWAS of hippocampal volume and additional data of a multicentre study in a large cohort of adolescents of European ancestry, we found supporting evidence for our results. Furthermore, allelic differences in rs4808611 and rs8170 were highly associated with differential mRNA expression in the cis-acting region. Associations with memory functioning indicate a possible functional importance of the identified risk variants. Our findings provide new insights into the genetic architecture of a brain structure closely linked to schizophrenia. In silico replication, mRNA expression and cognitive data provide additional support for the relevance of our findings. Identification of causal variants and their functional effects may unveil yet unknown players in the neurodevelopment and the pathogenesis of neuropsychiatric disorders.     

Genome-wide association study identified genetic variations and candidate genes for plant architecture component traits in Chinese upland cotton

Key message

Thirty significant associations between 22 SNPs and five plant architecture component traits in Chinese upland cotton were identified via GWAS. Four peak SNP loci located on chromosome D03 were simultaneously associated with more plant architecture component traits. A candidate gene, Gh_D03G0922, might be responsible for plant height in upland cotton.

Abstract

A compact plant architecture is increasingly required for mechanized harvesting processes in China. Therefore, cotton plant architecture is an important trait, and its components, such as plant height, fruit branch length and fruit branch angle, affect the suitability of a cultivar for mechanized harvesting. To determine the genetic basis of cotton plant architecture, a genome-wide association study (GWAS) was performed using a panel composed of 355 accessions and 93,250 single nucleotide polymorphisms (SNPs) identified using the specific-locus amplified fragment sequencing method. Thirty significant associations between 22 SNPs and five plant architecture component traits were identified via GWAS. Most importantly, four peak SNP loci located on chromosome D03 were simultaneously associated with more plant architecture component traits, and these SNPs were harbored in one linkage disequilibrium block. Furthermore, 21 candidate genes for plant architecture were predicted in a 0.95-Mb region including the four peak SNPs. One of these genes (Gh_D03G0922) was near the significant SNP D03_31584163 (8.40 kb), and its Arabidopsis homologs contain MADS-box domains that might be involved in plant growth and development. qRT-PCR showed that the expression of Gh_D03G0922 was upregulated in the apical buds and young leaves of the short and compact cotton varieties, and virus-induced gene silencing (VIGS) proved that the silenced plants exhibited increased PH. These results indicate that Gh_D03G0922 is likely the candidate gene for PH in cotton. The genetic variations and candidate genes identified in this study lay a foundation for cultivating moderately short and compact varieties in future Chinese cotton-breeding programs.

     

Major histocompatibility complex and other allergy-related candidate genes associated with insect bite hypersensitivity in Icelandic horses

Insect bite hypersensitivity (IBH) is an allergic dermatitis of horses caused by bites of insects. IBH is a multifactorial disease with contribution of genetic and environmental factors. Candidate gene association analysis of IBH was performed in a group of 89 Icelandic horses all born in Iceland and imported to Europe. Horses were classified in IBH-affected and non-affected based on clinical signs and history of recurrent dermatitis, and on the results of an in vitro sulfidoleukotriene (sLT)-release assay with Culicoides nubeculosus and Simulium vittatum extract. Different genetic markers were tested for association with IBH by the Fisher’s exact test. The effect of the major histocompatibility complex (MHC) gene region was studied by genotyping five microsatellites spanning the MHC region (COR112, COR113, COR114, UM011 and UMN-JH34-2), and exon 2 polymorphisms of the class II Eqca-DRA gene. Associations with Eqca-DRA and COR113 were identified (p < 0.05). In addition, a panel of 20 single nucleotide polymorphisms (SNPs) in 17 candidate allergy-related genes was tested. During the initial screen, no marker from the panel was significantly (p < 0.05) associated with IBH. Five SNPs associated with IBH at p < 0.10 were therefore used for analysis of combined genotypes. Out of them, SNPs located in the genes coding for the CD14 receptor (CD14), interleukin 23 receptor (IL23R), thymic stromal lymphopoietin (TSLP) and transforming growth factor beta 3 (TGFB3) molecules were associated with IBH as parts of complex genotypes. These results are supported by similar associations and by expression data from different horse populations and from human studies.     

Human Disease-Associated Genetic Variation Impacts Large Intergenic Non-Coding RNA Expression

Recently it has become clear that only a small percentage (7%) of disease-associated single nucleotide polymorphisms (SNPs) are located in protein-coding regions, while the remaining 93% are located in gene regulatory regions or in intergenic regions. Thus, the understanding of how genetic variations control the expression of non-coding RNAs (in a tissue-dependent manner) has far-reaching implications. We tested the association of SNPs with expression levels (eQTLs) of large intergenic non-coding RNAs (lincRNAs), using genome-wide gene expression and genotype data from five different tissues. We identified 112 cis-regulated lincRNAs, of which 45% could be replicated in an independent dataset. We observed that 75% of the SNPs affecting lincRNA expression (lincRNA cis-eQTLs) were specific to lincRNA alone and did not affect the expression of neighboring protein-coding genes. We show that this specific genotype-lincRNA expression correlation is tissue-dependent and that many of these lincRNA cis-eQTL SNPs are also associated with complex traits and diseases.     

In silico investigations on functional and haplotype tag SNPs associated with congenital long QT syndromes (LQTSs)

Single-nucleotide polymorphisms (SNPs) play a major role in the understanding of the genetic basis of many complex human diseases. It is still a major challenge to identify the functional SNPs in disease-related genes. In this review, the genetic variation that can alter the expression and the function of the genes, namely KCNQ1, KCNH2, SCN5A, KCNE1 and KCNE2, with the potential role for the development of congenital long QT syndrome (LQTS) was analyzed. Of the total of 3,309 SNPs in all five genes, 27 non-synonymous SNPs (nsSNPs) in the coding region and 44 SNPs in the 5′ and 3′ un-translated regions (UTR) were identified as functionally significant. SIFT and PolyPhen programs were used to analyze the nsSNPs and FastSNP; UTR scan programs were used to compute SNPs in the 5′ and 3′ untranslated regions. Of the five selected genes, KCNQ1 has the highest number of 26 haplotype blocks and 6 tag SNPs with a complete linkage disequilibrium value. The gene SCN5A has ten haplotype blocks and four tag SNPs. Both KCNE1 and KCNE2 genes have only one haplotype block and four tag SNPs. Four haplotype blocks and two tag SNPs were obtained for KCNH2 gene. Also, this review reports the copy number variations (CNVs), expressed sequence tags (ESTs) and genome survey sequences (GSS) of the selected genes. These computational methods are in good agreement with experimental works reported earlier concerning LQTS.     

Application of Gene Network Analysis Techniques Identifies AXIN1/PDIA2 and Endoglin Haplotypes Associated with Bicuspid Aortic Valve

Bicuspid Aortic Valve (BAV) is a highly heritable congenital heart defect. The low frequency of BAV (1% of general population) limits our ability to perform genome-wide association studies. We present the application of four a priori SNP selection techniques, reducing the multiple-testing penalty by restricting analysis to SNPs relevant to BAV in a genome-wide SNP dataset from a cohort of 68 BAV probands and 830 control subjects. Two knowledge-based approaches, CANDID and STRING, were used to systematically identify BAV genes, and their SNPs, from the published literature, microarray expression studies and a genome scan. We additionally tested Functionally Interpolating SNPs (fitSNPs) present on the array; the fourth consisted of SNPs selected by Random Forests, a machine learning approach. These approaches reduced the multiple testing penalty by lowering the fraction of the genome probed to 0.19% of the total, while increasing the likelihood of studying SNPs within relevant BAV genes and pathways. Three loci were identified by CANDID, STRING, and fitSNPS. A haplotype within the AXIN1-PDIA2 locus (p-value of 2.926×10⁻⁰⁶) and a haplotype within the Endoglin gene (p-value of 5.881×10⁻⁰⁴) were found to be strongly associated with BAV. The Random Forests approach identified a SNP on chromosome 3 in association with BAV (p-value 5.061×10⁻⁰⁶). The results presented here support an important role for genetic variants in BAV and provide support for additional studies in well-powered cohorts. Further, these studies demonstrate that leveraging existing expression and genomic data in the context of GWAS studies can identify biologically relevant genes and pathways associated with a congenital heart defect.     

Y Chromosome Gene Expression in the Blood of Male Patients With Ischemic Stroke Compared With Male Controls

BackgroundSex is suggested to be an important determinant of ischemic stroke risk factors, etiology, and outcome. However, the basis for this remains unclear. The Y chromosome is unique in males. Genes expressed in males on the Y chromosome that are associated with stroke may be important genetic contributors to the unique features of males with ischemic stroke, which would be helpful for explaining sex differences observed between men and women.ObjectiveWe compared Y chromosome gene expression in males with ischemic stroke and male controls.MethodsBlood samples were obtained from 40 male patients ≤3, 5, and 24 hours after ischemic stroke and from 41 male controls (July 2003–April 2007). RNA was isolated from blood and was processed using Affymetrix Human U133 Plus 2.0 expression arrays (Affymetrix Inc., Santa Clara, California). Y chromosome genes differentially expressed between male patients with stroke and male control subjects were identified using an ANCOVA adjusted for age and batch. A P < 0.05 and a fold change >1.2 were considered significant.ResultsSeven genes on the Y chromosome were differentially expressed in males with ischemic stroke compared with controls. Five of these genes (VAMP7, CSF2RA, SPRY3, DHRSX, and PLCXD1) are located on pseudoautosomal regions of the human Y chromosome. The other 2 genes (EIF1AY and DDX3Y) are located on the nonrecombining region of the human Y chromosome. The identified genes were associated with immunology, RNA metabolism, vesicle fusion, and angiogenesis.ConclusionsSpecific genes on the Y chromosome are differentially expressed in blood after ischemic stroke. These genes provide insight into potential molecular contributors to sex differences in ischemic stroke.     

Polymorphisms in recent GWA identified asthma genes CA10, SGK493, and CTNNA3 are associated with disease severity and treatment response in childhood asthma

Recent genome-wide association studies (GWAs) have identified several new genetic risk factors for asthma; however, their influence on disease behavior and treatment response is still unclear. The aim of our study was the association analysis of the most significant single nucleotide polymorphisms (SNPs) recently reported by GWAs in different phenotypes of childhood asthma and analysis of correlation between these SNPs and clinical parameters. We have genotyped 288 children with asthma and 276 healthy controls. We provided here first replication of bivariate associations between CA10 (p?=?0.001) and SGK493 (p?=?0.011) with asthma. In addition, we have identified new correlation between SNPs in CA10, SGK493, and CTNNA3 with asthma behavior and glucocorticoid treatment response. Asthma patients who carried G allele in SNP rs967676 in gene CA10 were associated with more pronounced airway obstruction, higher bronchial hyper-reactivity, and increased inflammation. Higher bronchial hyper-reactivity was also associated with C allele in SNP rs1440095 in gene SGK493 but only in nonatopic asthmatics. In addition, we found that patients who carried at least one T allele in SNP rs1786929 in CTNNA3 (p?=?0.022) and atopic patients who carried at least one G allele in SNP rs967676 in gene CA10 (p?=?0.034) had higher increase in pulmonary function after glucocorticoid therapy. Our results suggest genetic heterogeneity between atopic and nonatopic asthma. We provided further evidence that treatment response in childhood asthma is genetically predisposed, and we report here two novel SNPs in genes CA10 and CTNNA3 as potential pharmacogenetic biomarkers that could be used in personalized treatment in childhood asthma.