173 research outputs found

    Addition of multiple rare SNPs to known common variants improves the association between disease and gene in the Genetic Analysis Workshop 17 data

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    The upcoming release of new whole-genome genotyping technologies will shed new light on whether there is an associative effect of previously immeasurable rare variants on incidence of disease. For Genetic Analysis Workshop 17, our team focused on a statistical method to detect associations between gene-based multiple rare variants and disease status. We added a combination of rare SNPs to a common variant shown to have an influence on disease status. This method provides us with an enhanced ability to detect the effect of these rare variants, which, modeled alone, would normally be undetectable. Adjusting for significant clinical parameters, several genes were found to have multiple rare variants that were significantly associated with disease outcome

    Family-based association testing of OCD-associated SNPs of SLC1A1 in an autism sample

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    Reports identified the neuronal glutamate transporter gene, SLC1A1 (OMIM 133550, chromosome 9p24), as a positional and functional candidate gene for obsessive–compulsive disorder (OCD). The presence of obsessions and compulsions similar to OCD in autism, the identification of this region in a genome-wide linkage analysis of individuals with autism spectrum disorders (ASDs), and the hypothesized role of glutamate in ASDs make SLC1A1 a candidate gene for ASD as well. To test for association between SLC1A1 and autism, we typed three single nucleotide polymorphisms (SNPs, rs301430, rs301979, rs301434) previously associated with OCD in 86 strictly defined trios with autism. Family-Based Association Tests (FBAT) with additive and recessive models were used to check for association. Additionally, an rs301430–rs301979 haplotype identified for OCD was investigated. FBAT revealed nominally significant association between autism and one SNP under a recessive model. The G allele of rs301979 was undertransmitted (equivalent to overtransmission of the C allele under a dominant model) to individuals with autism ( Z =−2.47, P =0.01). The G allele was also undertransmitted in the T–G haplotype under the recessive model ( Z =−2.41, P =0.02). Both findings were also observed in the male-only sample. However, they did not withstand correction for multiple comparisons.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/58657/1/11_ftp.pd

    Exploring Case-Control Genetic Association Tests Using Phase Diagrams

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    Background: By a new concept called "phase diagram", we compare two commonly used genotype-based tests for case-control genetic analysis, one is a Cochran-Armitage trend test (CAT test at x=0.5x=0.5, or CAT0.5) and another (called MAX2) is the maximization of two chi-square test results: one from the two-by-two genotype count table that combines the baseline homozygotes and heterozygotes, and another from the table that combines heterozygotes with risk homozygotes. CAT0.5 is more suitable for multiplicative disease models and MAX2 is better for dominant/recessive models. Methods: We define the CAT0.5-MAX2 phase diagram on the disease model space such that regions where MAX2 is more powerful than CAT0.5 are separated from regions where the CAT0.5 is more powerful, and the task is to choose the appropriate parameterization to make the separation possible. Results: We find that using the difference of allele frequencies (δp\delta_p) and the difference of Hardy-Weinberg disequilibrium coefficients (δϵ\delta_\epsilon) can separate the two phases well, and the phase boundaries are determined by the angle tan−1(δp/δϵ)tan^{-1}(\delta_p/\delta_\epsilon), which is an improvement over the disease model selection using δϵ\delta_\epsilon only. Conclusions: We argue that phase diagrams similar to the one for CAT0.5-MAX2 have graphical appeals in understanding power performance of various tests, clarifying simulation schemes, summarizing case-control datasets, and guessing the possible mode of inheritance

    Genetic approaches to understanding the causes of stuttering

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    Stuttering is a common but poorly understood speech disorder. Evidence accumulated over the past several decades has indicated that genetic factors are involved, and genetic linkage studies have begun to identify specific chromosomal loci at which causative genes are likely to reside. A detailed investigation of one such region on chromosome 12 has identified mutations in the GNPTAB gene that are associated with stuttering in large families and in the general population. Subsequent studies identified mutations in the functionally related GNPTG and NAGPA genes. Mutations in these genes disrupt the lysosomal targeting pathway that generates the Mannose 6-phosphate signal, which directs a diverse group of enzymes to their target location in the lysosome of the cell. While mutations in these three genes can be identified in less than 10% of cases of familial stuttering, this knowledge allows a variety of new studies that can help identify the neuropathology that underlies this disorder

    Common variants in the regulative regions of GRIA1 and GRIA3 receptor genes are associated with migraine susceptibility

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    <p>Abstract</p> <p>Background</p> <p>Glutamate is the principal excitatory neurotransmitter in the central nervous system which acts by the activation of either ionotropic (AMPA, NMDA and kainate receptors) or G-protein coupled metabotropic receptors. Glutamate is widely accepted to play a major role in the path physiology of migraine as implicated by data from animal and human studies. Genes involved in synthesis, metabolism and regulation of both glutamate and its receptors could be, therefore, considered as potential candidates for causing/predisposing to migraine when mutated.</p> <p>Methods</p> <p>The association of polymorphic variants of <it>GRIA1</it>-<it>GRIA4 </it>genes which encode for the four subunits (GluR1-GluR4) of the alpha-amino-3- hydroxy-5-methyl-4-isoxazole-propionic acid (AMPA) receptor for glutamate was tested in migraineurs with and without aura (MA and MO) and healthy controls.</p> <p>Results</p> <p>Two variants in the regulative regions of <it>GRIA1 </it>(rs2195450) and <it>GRIA3 </it>(rs3761555) genes resulted strongly associated with MA (P = 0.00002 and P = 0.0001, respectively), but not associated with MO, suggesting their role in cortical spreading depression. Whereas the rs548294 variant in <it>GRIA1 </it>gene showed association primarily with MO phenotype, supporting the hypothesis that MA and MO phenotypes could be genetically related. These variants modify binding sites for transcription factors altering the expression of <it>GRIA1 </it>and <it>GRIA3 </it>genes in different conditions.</p> <p>Conclusions</p> <p>This study represents the first genetic evidence of a link between glutamate receptors and migraine.</p

    Preterm Birth in Caucasians Is Associated with Coagulation and Inflammation Pathway Gene Variants

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    Spontaneous preterm birth (<37 weeks gestation—PTB) occurs in ∼12% of pregnancies in the United States, and is the largest contributor to neonatal morbidity and mortality. PTB is a complex disease, potentially induced by several etiologic factors from multiple pathophysiologic pathways. To dissect the genetic risk factors of PTB a large-scale high-throughput candidate gene association study was performed examining 1536 SNP in 130 candidate genes from hypothesized PTB pathways. Maternal and fetal DNA from 370 US Caucasian birth-events (172 cases and 198 controls) was examined. Single locus, haplotype, and multi-locus association analyses were performed separately on maternal and fetal data. For maternal data the strongest associations were found in genes in the complement-coagulation pathway related to decidual hemorrhage in PTB. In this pathway 3 of 6 genes examined had SNPs significantly associated with PTB. These include factor V (FV) that was previously associated with PTB, factor VII (FVII), and tissue plasminogen activator (tPA). The single strongest effect was observed in tPA marker rs879293 with a significant allelic (p = 2.30×10−3) and genotypic association (p = 2.0×10−6) with PTB. The odds ratio (OR) for this SNP was 2.80 [CI 1.77–4.44] for a recessive model. Given that 6 of 8 markers in tPA were statistically significant, sliding window haplotype analyses were performed and revealed an associating 4 marker haplotype in tPA (p = 6.00×10−3). The single strongest effect in fetal DNA was observed in the inflammatory pathway at rs17121510 in the interleukin-10 receptor antagonist (IL-10RA) gene for allele (p = 0.01) and genotype (p = 3.34×10−4). The OR for the IL-10RA genotypic additive model was 1.92 [CI 1.15–3.19] (p = 2.00×10−3). Finally, exploratory multi-locus analyses in the complement and coagulation pathway were performed and revealed a potentially significant interaction between a marker in FV (rs2187952) and FVII (rs3211719) (p<0.001). These results support a role for genes in both the coagulation and inflammation pathways, and potentially different maternal and fetal genetic risks for PTB

    The non-invasive biopsy: will urinary proteomics make the renal tissue biopsy redundant?

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    Proteomics is a rapidly advancing technique which gives a functional insight into gene expression in living organisms. Urine is an ideal medium for study as it is readily available, easily obtained and less complex than other bodily fluids. Considerable progress has been made over the last 5 years in the study of urinary proteomics as a diagnostic tool for renal disease. The advantages of this technique over the traditional renal biopsy include accessibility, safety, the possibility of serial sampling, and the potential for non-invasive prognostic and diagnostic monitoring of disease and an individual’s response to treatment. Urinary proteomics is now moving from a discovery phase in small studies to a validation phase in much larger numbers of patients with renal disease. Whilst there are still some limitations in methodology, which are assessed in this review, the possibility of urinary proteomics replacing the invasive tissue biopsy for diagnosis of renal disease is becoming increasingly realistic

    Fine mapping of a linkage peak with integration of lipid traits identifies novel coronary artery disease genes on chromosome 5

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    Coronary artery disease (CAD), and one of its intermediate risk factors, dyslipidemia, possess a demonstrable genetic component, although the genetic architecture is incompletely defined. We previously reported a linkage peak on chromosome 5q31-33 for early-onset CAD where the strength of evidence for linkage was increased in families with higher mean low density lipoprotein-cholesterol (LDL-C). Therefore, we sought to fine-map the peak using association mapping of LDL-C as an intermediate disease-related trait to further define the etiology of this linkage peak. The study populations consisted of 1908 individuals from the CATHGEN biorepository of patients undergoing cardiac catheterization; 254 families (N = 827 individuals) from the GENECARD familial study of early-onset CAD; and 162 aorta samples harvested from deceased donors. Linkage disequilibrium-tagged SNPs were selected with an average of one SNP per 20 kb for 126.6-160.2 MB (region of highest linkage) and less dense spacing (one SNP per 50 kb) for the flanking regions (117.7-126.6 and 160.2-167.5 MB) and genotyped on all samples using a custom Illumina array. Association analysis of each SNP with LDL-C was performed using multivariable linear regression (CATHGEN) and the quantitative trait transmission disequilibrium test (QTDT; GENECARD). SNPs associated with the intermediate quantitative trait, LDL-C, were then assessed for association with CAD (i.e., a qualitative phenotype) using linkage and association in the presence of linkage (APL; GENECARD) and logistic regression (CATHGEN and aortas)

    Genetic association analysis of N-methyl-d-aspartate receptor subunit gene GRIN2B and clinical response to clozapine

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    OBJECTIVE: Approximately 30% of patients with schizophrenia fail to respond to antipsychotic therapy and are classified as having treatment-resistant schizophrenia. Clozapine is the most efficacious drug for treatment-resistant schizophrenia and may deliver superior therapeutic effects partly by modulating glutamate neurotransmission. Response to clozapine is highly variable and may depend on genetic factors as indicated by twin studies. We investigated eight polymorphisms in the N-methyl-d-aspartate glutamate receptor subunit gene GRIN2B with response to clozapine. METHODS: GRIN2B variants were genotyped using standard TaqMan procedures in 175 European patients with schizophrenia deemed resistant or intolerant to treatment. Response was assessed using change in Brief Psychiatric Rating Scale scores following six months of clozapine therapy. Categorical and continuous response was assessed using chi-squared test and analysis of covariance, respectively. RESULTS: No associations were observed between the variants and response to clozapine. A-allele carriers of rs1072388 responded marginally better to clozapine therapy than GG-homozygotes; however, the difference was not statistically significant (p = 0.067, uncorrected). CONCLUSIONS: Our findings do not support a role for these GRIN2B variants in altering response to clozapine in our sample. Investigation of additional glutamate variants in clozapine response is warranted. Copyright © 2016 John Wiley & Sons, Ltd
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