944 resultados para quantitative trait loci (QTL)


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A fractal method was introduced to quantitatively characterize the dispersibility of modified kaolinite (MK) and precipitated silica (PS) in styrene–butadiene rubber (SBR) matrix based on the lower magnification transmission electron microscopic images. The fractal dimension (FD) is greater, and the dispersion is worse. The fractal results showed that the dispersibility of MK in the latex blending sample is better than that in the mill blending samples. With the increase of kaolinite content, the FD increases from 1.713 to 1.800, and the dispersibility of kaolinite gradually decreases. There is a negative correlation between the dispersibility and loading content. With the decrease of MK and increase of PS, the FD significantly decreases from 1.735 to 1.496 and the dipersibility of kaolinite remarkably increases. The hybridization can improve the dispersibility of fillers in polymer matrix. The FD can be used to quantitatively characterize the aggregation and dispersion of kaolinite sheets in rubber matrix.

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Variation in body iron is associated with or causes diseases, including anaemia and iron overload. Here, we analyse genetic association data on biochemical markers of iron status from 11 European-population studies, with replication in eight additional cohorts (total up to 48,972 subjects). We find 11 genome-wide-significant (P<5 × 10−8) loci, some including known iron-related genes (​HFE, ​SLC40A1, ​TF, ​TFR2, ​TFRC, ​TMPRSS6) and others novel (​ABO, ​ARNTL, ​FADS2, ​NAT2, ​TEX14). SNPs at ​ARNTL, ​TF, and ​TFR2 affect iron markers in ​HFE C282Y homozygotes at risk for hemochromatosis. There is substantial overlap between our iron loci and loci affecting erythrocyte and lipid phenotypes. These results will facilitate investigation of the roles of iron in disease.

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Genome-wide association studies (GWAS) have identified 76 variants associated with prostate cancer risk predominantly in populations of European ancestry. To identify additional susceptibility loci for this common cancer, we conducted a meta-analysis of > 10 million SNPs in 43,303 prostate cancer cases and 43,737 controls from studies in populations of European, African, Japanese and Latino ancestry. Twenty-three new susceptibility loci were identified at association P < 5 × 10(-8); 15 variants were identified among men of European ancestry, 7 were identified in multi-ancestry analyses and 1 was associated with early-onset prostate cancer. These 23 variants, in combination with known prostate cancer risk variants, explain 33% of the familial risk for this disease in European-ancestry populations. These findings provide new regions for investigation into the pathogenesis of prostate cancer and demonstrate the usefulness of combining ancestrally diverse populations to discover risk loci for disease.

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This research has brought new scientific insight into the characteristics of airborne engineered nanoparticles, which is essential when considering their effects on human health. The key findings of the work were a harmonised and traceable protocol for the size characterisation of engineered nanoparticles, and quantification of their emissions and dynamics in workplaces. The novelty of this project is in coupling a comprehensive experimental measurement approach with innovative and effective data interpretation. Also, for the first time, the existence of a general trend in the emission of nanoparticles from a nanotechnology process was investigated.

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Despite substantial progress in measuring the 3D profile of anatomical variations in the human brain, their genetic and environmental causes remain enigmatic. We developed an automated system to identify and map genetic and environmental effects on brain structure in large brain MRI databases . We applied our multi-template segmentation approach ("Multi-Atlas Fluid Image Alignment") to fluidly propagate hand-labeled parameterized surface meshes into 116 scans of twins (60 identical, 56 fraternal), labeling the lateral ventricles. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps revealed 3D heritability patterns, and their significance, with and without adjustments for global brain scale. These maps visualized detailed profiles of environmental versus genetic influences on the brain, extending genetic models to spatially detailed, automatically computed, 3D maps.

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Inter-individual variation in facial shape is one of the most noticeable phenotypes in humans, and it is clearly under genetic regulation; however, almost nothing is known about the genetic basis of normal human facial morphology. We therefore conducted a genome-wide association study for facial shape phenotypes in multiple discovery and replication cohorts, considering almost ten thousand individuals of European descent from several countries. Phenotyping of facial shape features was based on landmark data obtained from three-dimensional head magnetic resonance images (MRIs) and two-dimensional portrait images. We identified five independent genetic loci associated with different facial phenotypes, suggesting the involvement of five candidate genes-PRDM16, PAX3, TP63, C5orf50, and COL17A1-in the determination of the human face. Three of them have been implicated previously in vertebrate craniofacial development and disease, and the remaining two genes potentially represent novel players in the molecular networks governing facial development. Our finding at PAX3 influencing the position of the nasion replicates a recent GWAS of facial features. In addition to the reported GWA findings, we established links between common DNA variants previously associated with NSCL/P at 2p21, 8q24, 13q31, and 17q22 and normal facial-shape variations based on a candidate gene approach. Overall our study implies that DNA variants in genes essential for craniofacial development contribute with relatively small effect size to the spectrum of normal variation in human facial morphology. This observation has important consequences for future studies aiming to identify more genes involved in the human facial morphology, as well as for potential applications of DNA prediction of facial shape such as in future forensic applications.

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Qualitative aspects of verbal fluency may be more useful in discerning the precise cause of any quantitative deficits in phonetic or category fluency, especially in the case of mild cognitive impairment (MCI), a possible intermediate stage between normal performance and Alzheimer's disease (AD). The aim of this study was to use both quantitative and qualitative (switches and clusters) methods to compare the phonetic and category verbal fluency performance of elderly adults with no cognitive impairment (n = 51), significant memory impairment (n = 16), and AD (n = 16). As expected, the AD group displayed impairments in all quantitative and qualitative measures of the two fluency tasks relative to their age- and education-matched peers. By contrast, the amnestic MCI group produced fewer animal names on the semantic fluency task than controls and showed normal performance on the phonetic fluency task. The MCI group's inferior category fluency performance was associated with a deficit in their category-switching rate rather than word cluster size. Overall, the results indicate that a semantic measure such as category fluency when used in conjunction with a test of episodic memory may increase the sensitivity for detecting preclinical AD. Future research using external cues and other measures of set shifting capacity may assist in clarifying the origin of the amnestic MCI-specific category-switching deficiency. Copyright

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The oily bittering Acheilognathus koreensis is a freshwater species that is endemic to Korea and is experiencing severe declines in natural populations as a result of habitat fragmentation and water pollution. For the conservation and restoration of this species, it is necessary to assess its genetic diversity at the population level. We developed 13 polymorphic microsatellite loci that were used to analyze the genetic diversity of two populations collected from the Kum River and the Tamjin River in Korea. All loci exhibited Mendelian inheritance patterns when examined in controlled crosses. Both populations revealed high levels of variability, with the number of alleles ranging from 3 to 20 and observed and expected heterozygosities ranging from 0.500 to 0.969 and from 0.529 to 0.938, respectively. None of the loci showed significant deviation from Hardy–Weinberg equilibrium, and one pair of loci showed significant linkage disequilibrium after Bonferroni correction. Pairwise F ST and genetic distance estimation showed significant differences between two populations. These results suggest that the microsatellites developed herein can be used to study the genetic diversity, population structure and conservation measure of A. koreensis.

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To further investigate susceptibility loci identified by genome-wide association studies, we genotyped 5,500 SNPs across 14 associated regions in 8,000 samples from a control group and 3 diseases: type 2 diabetes (T2D), coronary artery disease (CAD) and Graves' disease. We defined, using Bayes theorem, credible sets of SNPs that were 95% likely, based on posterior probability, to contain the causal disease-associated SNPs. In 3 of the 14 regions, TCF7L2 (T2D), CTLA4 (Graves' disease) and CDKN2A-CDKN2B (T2D), much of the posterior probability rested on a single SNP, and, in 4 other regions (CDKN2A-CDKN2B (CAD) and CDKAL1, FTO and HHEX (T2D)), the 95% sets were small, thereby excluding most SNPs as potentially causal. Very few SNPs in our credible sets had annotated functions, illustrating the limitations in understanding the mechanisms underlying susceptibility to common diseases. Our results also show the value of more detailed mapping to target sequences for functional studies. © 2012 Nature America, Inc. All rights reserved.

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Ankylosing spondylitis (AS) is a common inflammatory arthritis predominantly affecting the axial skeleton. Susceptibility to the disease is thought to be oligogenic. To identify the genes involved, we have performed a genomewide scan in 185 families containing 255 affected sibling pairs. Two-point and multipoint nonparametric linkage analysis was performed. Regions were identified showing "suggestive" or stronger linkage with the disease on chromosomes 1p, 2q, 6p, 9q, 10q, 16q, and 19q. The MHC locus was identified as encoding the greatest component of susceptibility, with an overall LOD score of 15.6. The strongest non-MHC linkage lies on chromosome 16q (overall LOD score 4.7). These results strongly support the presence of non-MHC genetic-susceptibility factors in AS and point to their likely locations.

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In this study, 1,833 systemic sclerosis (SSc) cases and 3,466 controls were genotyped with the Immunochip array. Classical alleles, amino acid residues, and SNPs across the human leukocyte antigen (HLA) region were imputed and tested. These analyses resulted in a model composed of six polymorphic amino acid positions and seven SNPs that explained the observed significant associations in the region. In addition, a replication step comprising 4,017 SSc cases and 5,935 controls was carried out for several selected non-HLA variants, reaching a total of 5,850 cases and 9,401 controls of European ancestry. Following this strategy, we identified and validated three SSc risk loci, including DNASE1L3 at 3p14, the SCHIP1-IL12A locus at 3q25, and ATG5 at 6q21, as well as a suggested association of the TREH-DDX6 locus at 11q23. The associations of several previously reported SSc risk loci were validated and further refined, and the observed peak of association in PXK was related to DNASE1L3. Our study has increased the number of known genetic associations with SSc, provided further insight into the pleiotropic effects of shared autoimmune risk factors, and highlighted the power of dense mapping for detecting previously overlooked susceptibility loci.

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Objective. To localize the regions containing genes that determine susceptibility to ankylosing spondylitis (AS). Methods. One hundred five white British families with 121 affected sibling pairs with AS were recruited, largely from the Royal National Hospital for Rheumatic Diseases AS database. A genome-wide linkage screen was undertaken using 254 highly polymorphic microsatellite markers from the Medical Research Council (UK) (MRC) set. The major histocompatibility complex (MHC) region was studied more intensively using 5 microsatellites lying within the HLA class III region and HLA-DRB1 typing. The Analyze package was used for 2-point analysis, and GeneHunter for multipoint analysis. Results. When only the MRC set was considered, 11 markers in 7 regions achieved a P value of ≤0.01. The maximum logarithm of odds score obtained was 3.8 (P = 1.4 x 10-5) using marker D6S273, which lies in the HLA class III region. A further marker used in mapping of the MHC class III region achieved a LOD score of 8.1 (P = 1 x 10-9). Nine of 118 affected sibling pairs (7.6%) did not share parental haplotypes identical by descent across the MHC, suggesting that only 31% of the susceptibility to AS is coded by genes linked to the MHC. The maximum non-MHC LOD score obtained was 2.6 (P = 0.0003) for marker D16S422. Conclusion. The results of this study confirm the strong linkage of the MHC with AS, and provide suggestive evidence regarding the presence and location of non-MHC genes influencing susceptibility to the disease.

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Objective. To examine whether the T cell receptor (TCR) A or TCRB loci exhibit linkage with disease in multiplex rheumatoid arthritis (RA) families. Methods. A linkage study was performed in 184 RA families from the UK Arthritis and Rheumatism Council Repository, each containing at least 1 affected sibpair. The microsatellites D14S50, TCRA, and D14S64 spanning the TCRA locus and D7S509, Vβ6.7, and D7S688 spanning the TCRB locus were used as DNA markers. The subjects were genotyped using a semiautomated polymerase chain reaction-based method. Two-point and multipoint linkage analyses were performed. Results. Nonparametric single-marker likelihood odds (LOD) scores were 0.49 (P = 0.07) for D14S50, 0.65 (P = 0.04) for TCRA, 0.07 (P = 0.29) for D14S64, 0.01 (P = 0.43) for D7S509, 0.0 (P = 0.50) for Vβ6.7, and 0.0 (P = 0.50) for D7S688. By multipoint analysis, there was no evidence of linkage at TCRB (LOD score 0), and the maximum LOD score at the TCRA locus was 0.37 (at D14S50). The presence of a susceptibility locus (LOD score < -2.0) was excluded, with lambda ≤ 1.8 at TCRA and ≤1.4 at TCRB. Conclusion. These linkage studies provide no significant evidence of a major germline-encoded TCRA or TCRB component of susceptibility to RA.

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Objective. To undertake a systematic wholegenome screen to identify regions exhibiting genetic linkage to rheumatoid arthritis (RA). Methods. Two hundred fifty-two RA-affected sibling pairs from 182 UK families were genotyped using 365 highly informative microsatellite markers. Microsatellite genotyping was performed using fluorescent polymerase chain reaction primers and semiautomated DNA sequencing technology. Linkage analysis was undertaken using MAPMAKER/SIBS for single-point and multipoint analysis. Results. Significant linkage (maximum logarithm of odds score 4.7 [P = 0.000003] at marker D6S276, 1 cM from HLA-DRB1) was identified around the major histocompatibility complex (MHC) region on chromosome 6. Suggestive linkage (P < 7.4 × 10-4) was identified on chromosome 6q by single- and multipoint analysis. Ten other sites of nominal linkage (P < 0.05) were identified on chromosomes 3p, 4q, 7p, 2 regions of 10q, 2 regions of 14q, 16p, 21q, and Xq by single-point analysis and on 3 sites (1q, 14q, and 14q) by multipoint analysis. Conclusion. Linkage to the MHC region was confirmed. Eleven non-HLA regions demonstrated evidence of suggestive or nominal linkage, but none reached the genome-wide threshold for significant linkage (P = 2.2 × 10-5). Results of previous genome screens have suggested that 6 of these regions may be involved in RA susceptibility.