926 resultados para genetic variants


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We extended genetic linkage analysis - an analysis widely used in quantitative genetics - to 3D images to analyze single gene effects on brain fiber architecture. We collected 4 Tesla diffusion tensor images (DTI) and genotype data from 258 healthy adult twins and their non-twin siblings. After high-dimensional fluid registration, at each voxel we estimated the genetic linkage between the single nucleotide polymorphism (SNP), Val66Met (dbSNP number rs6265), of the BDNF gene (brain-derived neurotrophic factor) with fractional anisotropy (FA) derived from each subject's DTI scan, by fitting structural equation models (SEM) from quantitative genetics. We also examined how image filtering affects the effect sizes for genetic linkage by examining how the overall significance of voxelwise effects varied with respect to full width at half maximum (FWHM) of the Gaussian smoothing applied to the FA images. Raw FA maps with no smoothing yielded the greatest sensitivity to detect gene effects, when corrected for multiple comparisons using the false discovery rate (FDR) procedure. The BDNF polymorphism significantly contributed to the variation in FA in the posterior cingulate gyrus, where it accounted for around 90-95% of the total variance in FA. Our study generated the first maps to visualize the effect of the BDNF gene on brain fiber integrity, suggesting that common genetic variants may strongly determine white matter integrity.

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Meta-analyses estimate a statistical effect size for a test or an analysis by combining results from multiple studies without necessarily having access to each individual study's raw data. Multi-site meta-analysis is crucial for imaging genetics, as single sites rarely have a sample size large enough to pick up effects of single genetic variants associated with brain measures. However, if raw data can be shared, combining data in a "mega-analysis" is thought to improve power and precision in estimating global effects. As part of an ENIGMA-DTI investigation, we use fractional anisotropy (FA) maps from 5 studies (total N=2, 203 subjects, aged 9-85) to estimate heritability. We combine the studies through meta-and mega-analyses as well as a mixture of the two - combining some cohorts with mega-analysis and meta-analyzing the results with those of the remaining sites. A combination of mega-and meta-approaches may boost power compared to meta-analysis alone.

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The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA-DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18-85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies. Protocols and templates are publicly available at (http://enigma.loni.ucla.edu/ongoing/dti-working-group/).

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Large multi-site image-analysis studies have successfully discovered genetic variants that affect brain structure in tens of thousands of subjects scanned worldwide. Candidate genes have also associated with brain integrity, measured using fractional anisotropy in diffusion tensor images (DTI). To evaluate the heritability and robustness of DTI measures as a target for genetic analysis, we compared 417 twins and siblings scanned on the same day on the same high field scanner (4-Tesla) with two protocols: (1) 94-directions; 2mm-thick slices, (2) 27-directions; 5mm-thickness. Using mean FA in white matter ROIs and FA skeletons derived using FSL, we (1) examined differences in voxelwise means, variances, and correlations among the measures; and (2) assessed heritability with structural equation models, using the classical twin design. FA measures from the genu of the corpus callosum were highly heritable, regardless of protocol. Genome-wide analysis of the genu mean FA revealed differences across protocols in the top associations.

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Delta opioid receptors are implicated in a variety of psychiatric and neurological disorders. These receptors play a key role in the reinforcing properties of drugs of abuse, and polymorphisms in OPRD1 (the gene encoding delta opioid receptors) are associated with drug addiction. Delta opioid receptors are also involved in protecting neurons against hypoxic and ischemic stress. Here, we first examined a large sample of 738 elderly participants with neuroimaging and genetic data from the Alzheimer's Disease Neuroimaging Initiative. We hypothesized that common variants in OPRD1 would be associated with differences in brain structure, particularly in regions relevant to addictive and neurodegenerative disorders. One very common variant (rs678849) predicted differences in regional brain volumes. We replicated the association of this single-nucleotide polymorphism with regional tissue volumes in a large sample of young participants in the Queensland Twin Imaging study. Although the same allele was associated with reduced volumes in both cohorts, the brain regions affected differed between the two samples. In healthy elderly, exploratory analyses suggested that the genotype associated with reduced brain volumes in both cohorts may also predict cerebrospinal fluid levels of neurodegenerative biomarkers, but this requires confirmation. If opiate receptor genetic variants are related to individual differences in brain structure, genotyping of these variants may be helpful when designing clinical trials targeting delta opioid receptors to treat neurological disorders.

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Identifying genetic variants influencing human brain structures may reveal new biological mechanisms underlying cognition and neuropsychiatric illness. The volume of the hippocampus is a biomarker of incipient Alzheimer's disease and is reduced in schizophrenia, major depression and mesial temporal lobe epilepsy. Whereas many brain imaging phenotypes are highly heritable, identifying and replicating genetic influences has been difficult, as small effects and the high costs of magnetic resonance imaging (MRI) have led to underpowered studies. Here we report genome-wide association meta-analyses and replication for mean bilateral hippocampal, total brain and intracranial volumes from a large multinational consortium. The intergenic variant rs7294919 was associated with hippocampal volume (12q24.22; N = 21,151; P = 6.70 × 10 -16) and the expression levels of the positional candidate gene TESC in brain tissue. Additionally, rs10784502, located within HMGA2, was associated with intracranial volume (12q14.3; N = 15,782; P = 1.12 × 10 -12). We also identified a suggestive association with total brain volume at rs10494373 within DDR2 (1q23.3; N = 6,500; P = 5.81 × 10 -7).

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Several genetic variants are thought to influence white matter (WM) integrity, measured with diffusion tensor imaging (DTI). Voxel based methods can test genetic associations, but heavy multiple comparisons corrections are required to adjust for searching the whole brain and for all genetic variants analyzed. Thus, genetic associations are hard to detect even in large studies. Using a recently developed multi-SNP analysis, we examined the joint predictive power of a group of 18 cholesterol-related single nucleotide polymorphisms (SNPs) on WM integrity, measured by fractional anisotropy. To boost power, we limited the analysis to brain voxels that showed significant associations with total serum cholesterol levels. From this space, we identified two genes with effects that replicated in individual voxel-wise analyses of the whole brain. Multivariate analyses of genetic variants on a reduced anatomical search space may help to identify SNPs with strongest effects on the brain from a broad panel of genes.

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Objective To investigate differences in genetic risk factors for rheumatoid arthritis (RA) in Han Chinese as compared with Europeans. Methods A genome-wide association study was conducted in China with 952 patients and 943 controls, and 32 variants were followed up in 2,132 patients and 2,553 controls. A transpopulation meta-analysis with results from a large European RA study was also performed to compare the genetic architecture across the 2 ethnic remote populations. Results Three non-major histocompatibility complex (non-MHC) loci were identified at the genome-wide significance level, the effect sizes of which were larger in anti-citrullinated protein antibody (ACPA)-positive patients than in ACPA-negative patients. These included 2 novel variants, rs12617656, located in an intron of DPP4 (odds ratio [OR] 1.56, P = 1.6 × 10 -21), and rs12379034, located in the coding region of CDK5RAP2 (OR 1.49, P = 1.1 × 10-16), as well as a variant at the known CCR6 locus, rs1854853 (OR 0.71, P = 6.5 × 10-15). The analysis of ACPA-positive patients versus ACPA-negative patients revealed that rs12617656 at the DPP4 locus showed a strong interaction effect with ACPAs (P = 5.3 × 10-18), and such an interaction was also observed for rs7748270 at the MHC locus (P = 5.9 × 10-8). The transpopulation meta-analysis showed genome-wide overlap and enrichment in association signals across the 2 populations, as confirmed by prediction analysis. Conclusion This study has expanded the list of alleles that confer risk of RA, provided new insight into the pathogenesis of RA, and added empirical evidence to the emerging polygenic nature of complex trait variation driven by common genetic variants. Copyright © 2014 by the American College of Rheumatology.

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Purpose of review Our understanding of the causation of the chondrocalcinosis and other disorders characterized by ectopic mineralization is rapidly increasing, and genetic studies have contributed substantially to recent major advances in the field. This review will discuss what is known about the genetics of chondrocalcinosis and what we have learned from genetic studies to date. Recent findings: Chondrocalcinosis is one of a family of conditions associated with ectopic mineralization. This family also includes disorders of mineralization of bone and spinal and other ligaments, and vascular calcification. There has been increasing evidence of the key role of transport and metabolism of inorganic pyrophosphate (PPi) in control of mineralization, and as the likely explanation for the association of a variety of genetic variants with chondrocalcinosis and ectopic mineralization elsewhere. This may be an overly simplistic view of this family of conditions, with recent evidence suggesting that, for example, ANKH variants may not all predispose to chondrocalcinosis by effects on PPi transport, but may also influence chondrocyte maturation. Summary: Understanding the control of the process of mineralization and its tissue specificity are important steps in the search for rational therapies for these conditions.

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Background To investigate potential cardiovascular and other effects of long-term pharmacological interleukin 1 (IL-1) inhibition, we studied genetic variants that produce inhibition of IL-1, a master regulator of inflammation. Methods We created a genetic score combining the effects of alleles of two common variants (rs6743376 and rs1542176) that are located upstream of IL1RN, the gene encoding the IL-1 receptor antagonist (IL-1Ra; an endogenous inhibitor of both IL-1α and IL-1β); both alleles increase soluble IL-1Ra protein concentration. We compared effects on inflammation biomarkers of this genetic score with those of anakinra, the recombinant form of IL-1Ra, which has previously been studied in randomised trials of rheumatoid arthritis and other inflammatory disorders. In primary analyses, we investigated the score in relation to rheumatoid arthritis and four cardiometabolic diseases (type 2 diabetes, coronary heart disease, ischaemic stroke, and abdominal aortic aneurysm; 453 411 total participants). In exploratory analyses, we studied the relation of the score to many disease traits and to 24 other disorders of proposed relevance to IL-1 signalling (746 171 total participants). Findings For each IL1RN minor allele inherited, serum concentrations of IL-1Ra increased by 0·22 SD (95% CI 0·18–0·25; 12·5%; p=9·3 × 10−33), concentrations of interleukin 6 decreased by 0·02 SD (−0·04 to −0·01; −1·7%; p=3·5 × 10−3), and concentrations of C-reactive protein decreased by 0·03 SD (−0·04 to −0·02; −3·4%; p=7·7 × 10−14). We noted the effects of the genetic score on these inflammation biomarkers to be directionally concordant with those of anakinra. The allele count of the genetic score had roughly log-linear, dose-dependent associations with both IL-1Ra concentration and risk of coronary heart disease. For people who carried four IL-1Ra-raising alleles, the odds ratio for coronary heart disease was 1·15 (1·08–1·22; p=1·8 × 10−6) compared with people who carried no IL-1Ra-raising alleles; the per-allele odds ratio for coronary heart disease was 1·03 (1·02–1·04; p=3·9 × 10−10). Per-allele odds ratios were 0·97 (0·95–0·99; p=9·9 × 10−4) for rheumatoid arthritis, 0·99 (0·97–1·01; p=0·47) for type 2 diabetes, 1·00 (0·98–1·02; p=0·92) for ischaemic stroke, and 1·08 (1·04–1·12; p=1·8 × 10−5) for abdominal aortic aneurysm. In exploratory analyses, we observed per-allele increases in concentrations of proatherogenic lipids, including LDL-cholesterol, but no clear evidence of association for blood pressure, glycaemic traits, or any of the 24 other disorders studied. Modelling suggested that the observed increase in LDL-cholesterol could account for about a third of the association observed between the genetic score and increased coronary risk. Interpretation Human genetic data suggest that long-term dual IL-1α/β inhibition could increase cardiovascular risk and, conversely, reduce the risk of development of rheumatoid arthritis. The cardiovascular risk might, in part, be mediated through an increase in proatherogenic lipid concentrations. Funding UK Medical Research Council, British Heart Foundation, UK National Institute for Health Research, National Institute for Health Research Cambridge Biomedical Research Centre, European Research Council, and European Commission Framework Programme 7.

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Background: The genetic basis for developing asthma has been extensively studied. However, association studies to date have mostly focused on mild to moderate disease and genetic risk factors for severe asthma remain unclear. Objective: To identify common genetic variants affecting susceptibility to severe asthma. Methods: A genome-wide association study was undertaken in 933 European ancestry individuals with severe asthma based on Global Initiative for Asthma (GINA) criteria 3 or above and 3346 clean controls. After standard quality control measures, the association of 480 889 genotyped single nucleotide polymorphisms (SNPs) was tested. To improve the resolution of the association signals identified, non-genotyped SNPs were imputed in these regions using a dense reference panel of SNP genotypes from the 1000 Genomes Project. Then replication of SNPs of interest was undertaken in a further 231 cases and 1345 controls and a meta-analysis was performed to combine the results across studies. Results: An association was confirmed in subjects with severe asthma of loci previously identified for association with mild to moderate asthma. The strongest evidence was seen for the ORMDL3/GSDMB locus on chromosome 17q12-21 (rs4794820, p=1.03×10 (-8)following meta-analysis) meeting genome-wide significance. Strong evidence was also found for the IL1RL1/IL18R1 locus on 2q12 (rs9807989, p=5.59×10 (-8) following meta-analysis) just below this threshold. No novel loci for susceptibility to severe asthma met strict criteria for genome-wide significance. Conclusions: The largest genome-wide association study of severe asthma to date was carried out and strong evidence found for the association of two previously identified asthma susceptibility loci in patients with severe disease. A number of novel regions with suggestive evidence were also identified warranting further study.

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Background and aims. Primary sclerosing cholangitis (PSC) is a chronic cholestatic liver disease characterized by progressive inflammation and fibrosis of the bile ducts eventually leading to biliary cirrhosis. Recent genetic studies in PSC have identified associations at 2q13, 2q35, 3p21, 4q27, 13q31 and suggestive association at 10p15. The aim of this study was to further characterize and refine the genetic architecture of PSC. Methods. We analyzed previously reported associated SNPs at four of these non-HLA loci and 59 SNPs tagging the IL-2/IL-21 (4q27) and IL2RA (10p15) loci in 992 UK PSC cases and 5162 healthy UK controls. Results. The most associated SNPs identified were rs3197999 (3p21 (MST1), p = 1.9 × 10 -6, OR A vs G = 1.28, 95% CI (1.16-1.42)); rs4147359 (10p15 (IL2RA), p = 2.6 × 10 -4, OR A vs G = 1.20, 95% CI (1.09-1.33)) and rs12511287 (4q27 (IL-2/IL-21), p = 3.0 × 10 -4, OR A vs T = 1.21, 95% CI (1.09-1.35)). In addition, we performed a meta-analysis for selected SNPs using published summary statistics from recent studies. We observed genome-wide significance for rs3197999 (3p21 (MST1), P combined = 3.8 × 10 -12) and rs4147359 (10p15 (IL2RA), P combined = 1.5 × 10 -8). Conclusion. We have for the first time confirmed the association of PSC with genetic variants at 10p15 (IL2RA) locus at genome-wide significance and replicated the associations at MST1 and IL-2/IL-21 loci in a large homogeneous UK population. These results strongly implicate the role of IL-2/IL2RA pathway in PSC and provide further confirmation of MST1 association. © Informa Healthcare.

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Peak bone mass achieved in adolescence is a determinant of bone mass in later life. In order to identify genetic variants affecting bone mineral density (BMD), we performed a genome-wide association study of BMD and related traits in 1518 children from the Avon Longitudinal Study of Parents and Children (ALSPAC). We compared results with a scan of 134 adults with high or low hip BMD. We identified associations with BMD in an area of chromosome 12 containing the Osterix (SP7) locus, a transcription factor responsible for regulating osteoblast differentiation (ALSPAC: P = 5.8 × 10-4; Australia: P = 3.7 × 10-4). This region has previously shown evidence of association with adult hip and lumbar spine BMD in an Icelandic population, as well as nominal association in a UK population. A meta-analysis of these existing studies revealed strong association between SNPs in the Osterix region and adult lumbar spine BMD (P = 9.9 × 10-11). In light of these findings, we genotyped a further 3692 individuals from ALSPAC who had whole body BMD and confirmed the association in children as well (P = 5.4 × 10-5). Moreover, all SNPs were related to height in ALSPAC children, but not weight or body mass index, and when height was included as a covariate in the regression equation, the association with total body BMD was attenuated. We conclude that genetic variants in the region of Osterix are associated with BMD in children and adults probably through primary effects on growth.

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Background MicroRNAs (miRNAs) are important small non-coding RNA molecules that regulate gene expression in cellular processes related to the pathogenesis of cancer. Genetic variation in miRNA genes could impact their synthesis and cellular effects and single nucleotide polymorphisms (SNPs) are one example of genetic variants studied in relation to breast cancer. Studies aimed at identifying miRNA SNPs (miR-SNPs) associated with breast malignancies could lead towards further understanding of the disease and to develop clinical applications for early diagnosis and treatment. Methods We genotyped a panel of 24 miR-SNPs using multiplex PCR and chip-based matrix assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) analysis in two Caucasian breast cancer case control populations (Primary population: 173 cases and 187 controls and secondary population: 679 cases and 301 controls). Association to breast cancer susceptibility was determined using chi-square (X 2 ) and odds ratio (OR) analysis. Results Statistical analysis showed six miR-SNPs to be non-polymorphic and twelve of our selected miR-SNPs to have no association with breast cancer risk. However, we were able to show association between rs353291 (located in MIR145) and the risk of developing breast cancer in two independent case control cohorts (p = 0.041 and p = 0.023). Conclusions Our study is the first to report an association between a miR-SNP in MIR145 and breast cancer risk in individuals of Caucasian background. This finding requires further validation through genotyping of larger cohorts or in individuals of different ethnicities to determine the potential significance of this finding as well as studies aimed to determine functional significance. Keywords: Association analysis; Breast cancer; microRNA; miR-SNPs; MIR145

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Pharmacogenetics deals with genetically determined variation in drug response. In this context, three phase I drug-metabolizing enzymes, CYP2D6, CYP2C9, and CYP2C19, have a central role, affecting the metabolism of about 20-30% of clinically used drugs. Since genes coding for these enzymes in human populations exhibit high genetic polymorphism, they are of major pharmacogenetic importance. The aims of this study were to develop new genotyping methods for CYP2D6, CYP2C9, and CYP2C19 that would cover the most important genetic variants altering the enzyme activity, and, for the first time, to describe the distribution of genetic variation at these loci on global and microgeographic scales. In addition, pharmacogenetics was applied to a postmortem forensic setting to elucidate the role of genetic variation in drug intoxications, focusing mainly on cases related to tricyclic antidepressants, which are commonly involved in fatal drug poisonings in Finland. Genetic variability data were obtained by genotyping new population samples by the methods developed based on PCR and multiplex single-nucleotide primer extension reaction, as well as by collecting data from the literature. Data consisted of 138, 129, and 146 population samples for CYP2D6, CYP2C9, and CYP2C19, respectively. In addition, over 200 postmortem forensic cases were examined with respect to drug and metabolite concentrations and genotypic variation at CYP2D6 and CYP2C19. The distribution of genetic variation within and among human populations was analyzed by descriptive statistics and variance analysis and by correlating the genetic and geographic distances using Mantel tests and spatial autocorrelation. The correlation between phenotypic and genotypic variation in drug metabolism observed in postmortem cases was also analyzed statistically. The genotyping methods developed proved to be informative, technically feasible, and cost-effective. Detailed molecular analysis of CYP2D6 genetic variation in a global survey of human populations revealed that the pattern of variation was similar to those of neutral genomic markers. Most of the CYP2D6 diversity was observed within populations, and the spatial pattern of variation was best described as clinal. On the other hand, genetic variants of CYP2D6, CYP2C9, and CYP2C19 associated with altered enzymatic activity could reach extremely high frequencies in certain geographic regions. Pharmacogenetic variation may also be significantly affected by population-specific demographic histories, as seen within the Finnish population. When pharmacogenetics was applied to a postmortem forensic setting, a correlation between amitriptyline metabolic ratios and genetic variation at CYP2D6 and CYP2C19 was observed in the sample material, even in the presence of confounding factors typical for these cases. In addition, a case of doxepin-related fatal poisoning was shown to be associated with a genetic defect at CYP2D6. Each of the genes studied showed a distinct variation pattern in human populations and high frequencies of altered activity variants, which may reflect the neutral evolution and/or selective pressures caused by dietary or environmental exposure. The results are relevant also from the clinical point of view since the genetic variation at CYP2D6, CYP2C9, and CYP2C19 already has a range of clinical applications, e.g. in cancer treatment and oral anticoagulation therapy. This study revealed that pharmacogenetics may also contribute valuable information to the medicolegal investigation of sudden, unexpected deaths.