62 resultados para Association Studies

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct or analysis.

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Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

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Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence, the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association (STREGA) studies initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

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Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

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Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information into the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and issues of data volume that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

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Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

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Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

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To identify novel quantitative trait loci (QTL) within horses, we performed genome-wide association studies (GWAS) based on sequence-level genotypes for conformation and performance traits in the Franches-Montagnes (FM) horse breed. Sequence-level genotypes of FM horses were derived by re-sequencing 30 key founders and imputing 50K data of genotyped horses. In total, we included 1077 FM horses genotyped for ~4 million SNPs and their respective de-regressed breeding values of the traits in the analysis. Based on this dataset, we identified a total of 14 QTL associated with 18 conformation traits and one performance trait. Therefore, our results suggest that the application of sequence-derived genotypes increases the power to identify novel QTL which were not identified previously based on 50K SNP chip data.

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Elevated concentrations of albumin in the urine, albuminuria, are a hallmark of diabetic kidney disease and associate with increased risk for end-stage renal disease and cardiovascular events. To gain insight into the pathophysiological mechanisms underlying albuminuria, we conducted meta-analyses of genome-wide association studies and independent replication in up to 5,825 individuals of European ancestry with diabetes mellitus and up to 46,061 without diabetes, followed by functional studies. Known associations of variants in CUBN, encoding cubilin, with the urinary albumin-to-creatinine ratio (UACR) were confirmed in the overall sample (p=2.4*10(-10)). Gene-by-diabetes interactions were detected and confirmed for variants in HS6ST1 and near RAB38/CTSC. SNPs at these loci demonstrated a genetic effect on UACR in individuals with but not without diabetes. The change in average UACR per minor allele was 21% for HS6ST1 and 13% for RAB38/CTSC (p=6.3*10(-7) and 5.8*10(-7), respectively). Experiments using streptozotocin-treated diabetic Rab38 knockout and control rats showed higher urinary albumin concentrations and reduced amounts of megalin and cubilin at the proximal tubule cell surface in Rab38 knockout vs. control rats. Relative expression of RAB38 was higher in tubuli of patients with diabetic kidney disease compared to controls. The loci identified here confirm known and highlight novel pathways influencing albuminuria.

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Genome-wide association studies (GWAS) have identified numerous single-nucleotide polymorphisms (SNPs) at four loci (SNCA, PARK16, LRRK2, BST1) that can modulate the risk of Parkinson's disease (PD). The strength of these associations has yet to be clarified in Mainland China. Ethnic specific effect is an important consideration in GWAS analysis. Using a case-control methodology, we genotyped multiple SNPs at these four loci to investigate their association with risk of PD in Mainland China. A total of 1,146 study subjects comprising 636 patients with PD and 510 unrelated healthy controls were recruited. The minor alleles at SNPs rs894278, rs1994090, rs2046932, rs4698412, and rs7304279 were found to be significantly higher in cases than in controls, while the minor alleles were found to significantly reduce the risk of developing PD at SNPs rs823128, rs823156, rs6532194, rs1191532, and rs16856139. These associations remained after taking into considerations the effects of age and gender. We showed that multiple SNPs at LRRK2 and SNCA increase risk of PD, while PARK16 SNPs are associated with a lower risk of PD in China. Our study findings will contribute to further research using GWAS-linked data and research on ethnic specific effect of common variants.

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The heritability of attention deficit hyperactivity disorder (ADHD) is approximately 0.8. Despite several larger scale attempts, genome-wide association studies (GWAS) have not led to the identification of significant results. We performed a GWAS based on 495 German young patients with ADHD (according to DSM-IV criteria; Human660W-Quadv1; Illumina, San Diego, CA) and on 1,300 population-based adult controls (HumanHap550v3; Illumina). Some genes neighboring the single nucleotide polymorphisms (SNPs) with the lowest P-values (best P-value: 8.38 × 10(-7)) have potential relevance for ADHD (e.g., glutamate receptor, metabotropic 5 gene, GRM5). After quality control, the 30 independent SNPs with the lowest P-values (P-values ≤ 7.57 × 10(-5) ) were chosen for confirmation. Genotyping of these SNPs in up to 320 independent German families comprising at least one child with ADHD revealed directionally consistent effect-size point estimates for 19 (10 not consistent) of the SNPs. In silico analyses of the 30 SNPs in the largest meta-analysis so far (2,064 trios, 896 cases, and 2,455 controls) revealed directionally consistent effect-size point estimates for 16 SNPs (11 not consistent). None of the combined analyses revealed a genome-wide significant result. SNPs in previously described autosomal candidate genes did not show significantly lower P-values compared to SNPs within random sets of genes of the same size. We did not find genome-wide significant results in a GWAS of German children with ADHD compared to controls. The second best SNP is located in an intron of GRM5, a gene located within a recently described region with an infrequent copy number variation in patients with ADHD.

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Background Three non-synonymous single nucleotide polymorphisms (Q223R, K109R and K656N) of the leptin receptor gene (LEPR) have been tested for association with obesity-related outcomes in multiple studies, showing inconclusive results. We performed a systematic review and meta-analysis on the association of the three LEPR variants with BMI. In addition, we analysed 15 SNPs within the LEPR gene in the CoLaus study, assessing the interaction of the variants with sex. Methodology/Principal Findings We searched electronic databases, including population-based studies that investigated the association between LEPR variants Q223R, K109R and K656N and obesity- related phenotypes in healthy, unrelated subjects. We furthermore performed meta-analyses of the genotype and allele frequencies in case-control studies. Results were stratified by SNP and by potential effect modifiers. CoLaus data were analysed by logistic and linear regressions and tested for interaction with sex. The meta-analysis of published data did not show an overall association between any of the tested LEPR variants and overweight. However, the choice of a BMI cut-off value to distinguish cases from controls was crucial to explain heterogeneity in Q223R. Differences in allele frequencies across ethnic groups are compatible with natural selection of derived alleles in Q223R and K109R and of the ancient allele in K656N in Asians. In CoLaus, the rs10128072, rs3790438 and rs3790437 variants showed interaction with sex for their association with overweight, waist circumference and fat mass in linear regressions. Conclusions Our systematic review and analysis of primary data from the CoLaus study did not show an overall association between LEPR SNPs and overweight. Most studies were underpowered to detect small effect sizes. A potential effect modification by sex, population stratification, as well as the role of natural selection should be addressed in future genetic association studies.

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The level of body iron storage and the erythropoietic need for iron are indicated by the serum levels of ferritin and soluble transferrin receptor (sTfR), respectively. A meta-analysis of five genome-wide association studies on sTfR and ferritin revealed novel association to the PCSK7 and TMPRSS6 loci for sTfR and the HFE locus for both parameters. The PCSK7 association was the most significant (rs236918, P = 1.1 × 10E-27) suggesting that proprotein convertase 7, the gene product of PCSK7, may be involved in sTfR generation and/or iron homeostasis. Conditioning the sTfR analyses on transferrin saturation abolished the HFE signal and substantially diminished the TMPRSS6 signal while the PCSK7 association was unaffected, suggesting that the former may be mediated by transferrin saturation whereas the PCSK7-associated effect on sTfR generation appears to be more direct.

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We identified a bipolar disorder (BPD) susceptibility region on chromosome 3q29 in a genome-wide linkage scan (Bailer et al. 2002 (Biol Psychiatry 52: 40), NPL-score 4.09) and follow-up linkage analysis (Schosser et al. 2004 (J Psychiatr Res 38(3): 357), NPL-scores >3 with five markers). These findings were supported by further fine-mapping of this region (Schosser et al. 2007 (Eur Neuropsychopharmacol 17(6-7): 501)), finding NPL-scores >3.9 with SNPs (single nucleotide polymorphisms) spanning a region of 3.46 Mbp in BPD families. Since genetic association studies are more powerful than linkage studies for detecting susceptibility genes of small effect size, we aimed to replicate these findings in an independent case-control sample collected in London (UK) and Vienna (Austria).

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Lung function measures are heritable, predict mortality and are relevant in diagnosis of chronic obstructive pulmonary disease (COPD). COPD and asthma are diseases of the airways with major public health impacts and each have a heritable component. Genome-wide association studies of SNPs have revealed novel genetic associations with both diseases but only account for a small proportion of the heritability. Complex copy number variation may account for some of the missing heritability. A well-characterised genomic region of complex copy number variation contains beta-defensin genes (DEFB103, DEFB104 and DEFB4), which have a role in the innate immune response. Previous studies have implicated these and related genes as being associated with asthma or COPD. We hypothesised that copy number variation of these genes may play a role in lung function in the general population and in COPD and asthma risk. We undertook copy number typing of this locus in 1149 adult and 689 children using a paralogue ratio test and investigated association with COPD, asthma and lung function. Replication of findings was assessed in a larger independent sample of COPD cases and smoking controls. We found evidence for an association of beta-defensin copy number with COPD in the adult cohort (OR = 1.4, 95%CI:1.02-1.92, P = 0.039) but this finding, and findings from a previous study, were not replicated in a larger follow-up sample(OR = 0.89, 95%CI:0.72-1.07, P = 0.217). No robust evidence of association with asthma in children was observed. We found no evidence for association between beta-defensin copy number and lung function in the general populations. Our findings suggest that previous reports of association of beta-defensin copy number with COPD should be viewed with caution. Suboptimal measurement of copy number can lead to spurious associations. Further beta-defensin copy number measurement in larger sample sizes of COPD cases and children with asthma are needed.