49 research outputs found

    Complicated narratives of “Korean-ness”: Towards strategic provisionality in parental involvement

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    The purpose of this paper is to advance the discourse on parental involvement drawing from Butlerian notion of strategic provisionality. In developing a new approach to understanding cultural differences and their relation to Korean parental involvement, the authors analyze qualitative and quantitative data from five New York metropolitan elementary schools. The authors examine the ways in which ‘Korean-ness’ and Korean parental involvement are discursively constructed and embodied in sociopolitical and historical contexts in the United States. We present two themes related to Korean parental involvement: (a) the double-edged component of respect for teachers and (b) biopolitics related to English language and parental involvement. By challenging normalized understanding about Korean-ness, the authors suggest a different approach to ethnoepistemology in order to enrich discourses concerning parental involvement and ethnic/racial studies

    High resolution linkage and association study of quantitative trait loci

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    As a large number of single nucleotide polymorphisms (SNPs) and microsatellite markers are available, high resolution mapping employing multiple markers or multiple allele markers is an important step to identify quantitative trait locus (QTL) of complex human disease. For many complex diseases, quantitative phenotype values contain more information than dichotomous traits do. Much research has been done on conducting high resolution mapping using information of linkage and linkage disequilibrium. The most commonly employed approaches for mapping QTL are pedigree-based linkage analysis and population-based association analysis. As one of the methods dealing with multiple alleles markers, mixed models are developed to work out family-based association study with the information of transmitted allele and nontransmitted allele from one parent to offspring. For multiple markers, variance component models are proposed to perform association study and linkage analysis simultaneously. Linkage analysis provides suggestive linkage based on a broad chromosome region and is robust to population admixtures. One the other hand, allelic association due to linkage disequilibrium (LD) usually operates over very short genetic distance, but is affected by population stratification. Combining both approaches plays a synergistic role in overcoming their limitations and in increasing the efficiency and effectiveness of gene mapping

    Changes in predicted protein disorder tendency may contribute to disease risk

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    <p>Abstract</p> <p>Background</p> <p>Recent studies suggest that many proteins or regions of proteins lack 3D structure. Defined as intrinsically disordered proteins, these proteins/peptides are functionally important. Recent advances in next generation sequencing technologies enable genome-wide identification of novel nucleotide variations in a specific population or cohort.</p> <p>Results</p> <p>Using the exonic single nucleotide variations (SNVs) identified in the 1,000 Genomes Project and distributed by the Genetic Analysis Workshop 17, we systematically analysed the genetic and predicted disorder potential features of the non-synonymous variations. The result of experiments suggests that a significant change in the tendency of a protein region to be structured or disordered caused by SNVs may lead to malfunction of such a protein and contribute to disease risk.</p> <p>Conclusions</p> <p>After validation with functional SNVs on the traits distributed by GAW17, we conclude that it is valuable to consider structure/disorder tendencies while prioritizing and predicting mechanistic effects arising from novel genetic variations.</p

    Identification of multiple rare variants associated with a disease

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    Identifying rare variants that are responsible for complex disease has been promoted by advances in sequencing technologies. However, statistical methods that can handle the vast amount of data generated and that can interpret the complicated relationship between disease and these variants have lagged. We apply a zero-inflated Poisson regression model to take into account the excess of zeros caused by the extremely low frequency of the 24,487 exonic variants in the Genetic Analysis Workshop 17 data. We grouped the 697 subjects in the data set as Europeans, Asians, and Africans based on principal components analysis and found the total number of rare variants per gene for each individual. We then analyzed these collapsed variants based on the assumption that rare variants are enriched in a group of people affected by a disease compared to a group of unaffected people. We also tested the hypothesis with quantitative traits Q1, Q2, and Q4. Analyses performed on the combined 697 individuals and on each ethnic group yielded different results. For the combined population analysis, we found that UGT1A1, which was not part of the simulation model, was associated with disease liability and that FLT1, which was a causal locus in the simulation model, was associated with Q1. Of the causal loci in the simulation models, FLT1 and KDR were associated with Q1 and VNN1 was correlated with Q2. No significant genes were associated with Q4. These results show the feasibility and capability of our new statistical model to detect multiple rare variants influencing disease risk

    Racial differences in sensitivity of blood pressure to aldosterone

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    Blacks in comparison with whites are at risk for a more serious form of hypertension with high rates of complications. Greater sodium retention is thought to underlie the blood pressure (BP)-determining physiology of blacks, but specific mechanisms have not been identified. In a prospective observational study of BP, 226 black children and 314 white children (mean age, 10.6 years) were enrolled initially. Assessments were repeated in 85 blacks and 136 whites after reaching adulthood (mean age, 31 years). The relationship of BP to plasma aldosterone concentration in the context of the prevailing level of plasma renin activity was studied in blacks and whites. In a secondary interventional study, 9-α fludrocortisone was administered for 2 weeks to healthy adult blacks and whites to simulate hyperaldosteronism. BP responses in the 2 race groups were then compared. Although black children had lower levels of plasma renin activity and plasma aldosterone, their BP was positively associated with the plasma aldosterone concentration, an effect that increased as plasma renin activity decreased (P=0.004). Data from black adults yielded similar results. No similar relationship was observed in whites. In the interventional study, 9-α fludrocortisone increased BP in blacks but not in whites. In conclusion, aldosterone sensitivity is a significant determinant of BP in young blacks. Although its role in establishing the risk of hypertension is not known, it could be as relevant as the actual level of aldosterone

    Allelic based gene-gene interactions in rheumatoid arthritis

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    The detection of gene-gene interaction is an important approach to understand the etiology of rheumatoid arthritis (RA). The goal of this study is to identify gene-gene interaction of SNPs at the allelic level contributing to RA using real data sets (Problem 1) of North American Rheumatoid Arthritis Consortium (NARAC) provided by Genetic Analysis Workshop 16 (GAW16). We applied our novel method that can detect the interaction by a definition of nonrandom association of alleles that occurs when the contribution to RA of a particular allele inherited in one gene depends on a particular allele inherited at other unlinked genes. Starting with 639 single-nucleotide polymorphisms (SNPs) from 26 candidate genes, we identified ten two-way interacting genes and one case of three-way interacting genes. SNP rs2476601 on PTPN22 interacts with rs2306772 on SLC22A4, which interacts with rs881372 on TRAF1 and rs2900180 on C5, respectively. SNP rs2900180 on C5 interacts with rs2242720 on RUNX1, which interacts with rs881375 on TRAF1. Furthermore, rs2476601 on PTPN22 also interacts with three SNPs (rs2905325, rs1476482, and rs2106549) in linkage disequilibrium (LD) on IL6. The other three SNPs (rs2961280, rs2961283, and rs2905308) in LD on IL6 interact with two SNPs (rs477515 and rs2516049) on HLA-DRB1. SNPs rs660895 and rs532098 on HLA-DRB1 interact with rs2834779 and four SNPs in LD on RUNX1. Three-way interacting genes of rs10229203 on IL6, rs4816502 on RUNX1, and rs10818500 on C5 were also detected

    A comparison study of multivariate fixed models and Gene Association with Multiple Traits (GAMuT) for nextâ generation sequencing

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    In this paper, extensive simulations are performed to compare two statistical methods to analyze multiple correlated quantitative phenotypes: (1) approximate Fâ distributed tests of multivariate functional linear models (MFLM) and additive models of multivariate analysis of variance (MANOVA), and (2) Gene Association with Multiple Traits (GAMuT) for association testing of highâ dimensional genotype data. It is shown that approximate Fâ distributed tests of MFLM and MANOVA have higher power and are more appropriate for major gene association analysis (i.e., scenarios in which some genetic variants have relatively large effects on the phenotypes); GAMuT has higher power and is more appropriate for analyzing polygenic effects (i.e., effects from a large number of genetic variants each of which contributes a small amount to the phenotypes). MFLM and MANOVA are very flexible and can be used to perform association analysis for (i) rare variants, (ii) common variants, and (iii) a combination of rare and common variants. Although GAMuT was designed to analyze rare variants, it can be applied to analyze a combination of rare and common variants and it performs well when (1) the number of genetic variants is large and (2) each variant contributes a small amount to the phenotypes (i.e., polygenes). MFLM and MANOVA are fixed effect models that perform well for major gene association analysis. GAMuT can be viewed as an extension of sequence kernel association tests (SKAT). Both GAMuT and SKAT are more appropriate for analyzing polygenic effects and they perform well not only in the rare variant case, but also in the case of a combination of rare and common variants. Data analyses of European cohorts and the Trinity Students Study are presented to compare the performance of the two methods.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135654/1/gepi22014_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135654/2/gepi22014-sup0001-Suppmat.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135654/3/gepi22014.pd

    Alcohol use disorder is associated with DNA methylation-based shortening of telomere length and regulated by TESPA1:implications for aging

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    Chronic heavy alcohol consumption is associated with increased mortality and morbidity and often leads to premature aging; however, the mechanisms of alcohol-associated cellular aging are not well understood. In this study, we used DNA methylation derived telomere length (DNAmTL) as a novel approach to investigate the role of alcohol use on the aging process. DNAmTL was estimated by 140 cytosine phosphate guanines (CpG) sites in 372 individuals with alcohol use disorder (AUD) and 243 healthy controls (HC) and assessed using various endophenotypes and clinical biomarkers. Validation in an independent sample of DNAmTL on alcohol consumption was performed (N = 4219). Exploratory genome-wide association studies (GWAS) on DNAmTL were also performed to identify genetic variants contributing to DNAmTL shortening. Top GWAS findings were analyzed using in-silico expression quantitative trait loci analyses and related to structural MRI hippocampus volumes of individuals with AUD. DNAmTL was 0.11-kilobases shorter per year in AUD compared to HC after adjustment for age, sex, race, and blood cell composition (p = 4.0 × 10(−12)). This association was partially attenuated but remained significant after additionally adjusting for BMI, and smoking status (0.06 kilobases shorter per year, p = 0.002). DNAmTL shortening was strongly associated with chronic heavy alcohol use (ps < 0.001), elevated gamma-glutamyl transferase (GGT), and aspartate aminotransferase (AST) (ps < 0.004). Comparison of DNAmTL with PCR-based methods of assessing TL revealed positive correlations (R = 0.3, p = 2.2 × 10(−5)), highlighting the accuracy of DNAmTL as a biomarker. The GWAS meta-analysis identified a single nucleotide polymorphism (SNP), rs4374022 and 18 imputed ones in Thymocyte Expressed, Positive Selection Associated 1(TESPA1), at the genome-wide level (p = 3.75 × 10(−8)). The allele C of rs4374022 was associated with DNAmTL shortening, lower hippocampus volume (p < 0.01), and decreased mRNA expression in hippocampus tissue (p = 0.04). Our study demonstrates DNAmTL-related aging acceleration in AUD and suggests a functional role for TESPA1 in regulating DNAmTL length, possibly via the immune system with subsequent biological effects on brain regions negatively affected by alcohol and implicated in aging

    Epigenome-wide association study of alcohol consumption in N = 8161 individuals and relevance to alcohol use disorder pathophysiology:identification of the cystine/glutamate transporter SLC7A11 as a top target

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    Alcohol misuse is common in many societies worldwide and is associated with extensive morbidity and mortality, often leading to alcohol use disorders (AUD) and alcohol-related end-organ damage. The underlying mechanisms contributing to the development of AUD are largely unknown; however, growing evidence suggests that alcohol consumption is strongly associated with alterations in DNA methylation. Identification of alcohol-associated methylomic variation might provide novel insights into pathophysiology and novel treatment targets for AUD. Here we performed the largest single-cohort epigenome-wide association study (EWAS) of alcohol consumption to date (N = 8161) and cross-validated findings in AUD populations with relevant endophenotypes, as well as alcohol-related animal models. Results showed 2504 CpGs significantly associated with alcohol consumption (Bonferroni p value < 6.8 × 10(−8)) with the five leading probes located in SLC7A11 (p = 7.75 × 10(−108)), JDP2 (p = 1.44 × 10(−56)), GAS5 (p = 2.71 × 10(−47)), TRA2B (p = 3.54 × 10(−42)), and SLC43A1 (p = 1.18 × 10(−40)). Genes annotated to associated CpG sites are implicated in liver and brain function, the cellular response to alcohol and alcohol-associated diseases, including hypertension and Alzheimer’s disease. Two-sample Mendelian randomization confirmed the causal relationship of consumption on AUD risk (inverse variance weighted (IVW) p = 5.37 × 10(−09)). A methylation-based predictor of alcohol consumption was able to discriminate AUD cases in two independent cohorts (p = 6.32 × 10(−38) and p = 5.41 × 10(−14)). The top EWAS probe cg06690548, located in the cystine/glutamate transporter SLC7A11, was replicated in an independent cohort of AUD and control participants (N = 615) and showed strong hypomethylation in AUD (p < 10(−17)). Decreased CpG methylation at this probe was consistently associated with clinical measures including increased heavy drinking days (p < 10(−4)), increased liver function enzymes (GGT (p = 1.03 × 10(−21)), ALT (p = 1.29 × 10(−6)), and AST (p = 1.97 × 10(−8))) in individuals with AUD. Postmortem brain analyses documented increased SLC7A11 expression in the frontal cortex of individuals with AUD and animal models showed marked increased expression in liver, suggesting a mechanism by which alcohol leads to hypomethylation-induced overexpression of SLC7A11. Taken together, our EWAS discovery sample and subsequent validation of the top probe in AUD suggest a strong role of abnormal glutamate signaling mediated by methylomic variation in SLC7A11. Our data are intriguing given the prominent role of glutamate signaling in brain and liver and might provide an important target for therapeutic intervention
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