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Sökning: WFRF:(Cadby Gemma) > Hayward Caroline

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1.
  • Artigas Soler, María, et al. (författare)
  • Genome-wide association and large-scale follow up identifies 16 new loci influencing lung function.
  • 2011
  • Ingår i: Nature genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 43:11, s. 1082-90
  • Tidskriftsartikel (refereegranskat)abstract
    • Pulmonary function measures reflect respiratory health and are used in the diagnosis of chronic obstructive pulmonary disease. We tested genome-wide association with forced expiratory volume in 1 second and the ratio of forced expiratory volume in 1 second to forced vital capacity in 48,201 individuals of European ancestry with follow up of the top associations in up to an additional 46,411 individuals. We identified new regions showing association (combined P < 5 × 10(-8)) with pulmonary function in or near MFAP2, TGFB2, HDAC4, RARB, MECOM (also known as EVI1), SPATA9, ARMC2, NCR3, ZKSCAN3, CDC123, C10orf11, LRP1, CCDC38, MMP15, CFDP1 and KCNE2. Identification of these 16 new loci may provide insight into the molecular mechanisms regulating pulmonary function and into molecular targets for future therapy to alleviate reduced lung function.
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2.
  • Berndt, Sonja I., et al. (författare)
  • Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture
  • 2013
  • Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:5, s. 501-U69
  • Tidskriftsartikel (refereegranskat)abstract
    • Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.
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3.
  • Obeidat, Ma'en, et al. (författare)
  • A Comprehensive Evaluation of Potential Lung Function Associated Genes in the SpiroMeta General Population Sample
  • 2011
  • Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 6:5, s. e19382-
  • Tidskriftsartikel (refereegranskat)abstract
    • Rationale: Lung function measures are heritable traits that predict population morbidity and mortality and are essential for the diagnosis of chronic obstructive pulmonary disease (COPD). Variations in many genes have been reported to affect these traits, but attempts at replication have provided conflicting results. Recently, we undertook a meta-analysis of Genome Wide Association Study (GWAS) results for lung function measures in 20,288 individuals from the general population (the SpiroMeta consortium). Objectives: To comprehensively analyse previously reported genetic associations with lung function measures, and to investigate whether single nucleotide polymorphisms (SNPs) in these genomic regions are associated with lung function in a large population sample. Methods: We analysed association for SNPs tagging 130 genes and 48 intergenic regions (+/-10 kb), after conducting a systematic review of the literature in the PubMed database for genetic association studies reporting lung function associations. Results: The analysis included 16,936 genotyped and imputed SNPs. No loci showed overall significant association for FEV1 or FEV1/FVC traits using a carefully defined significance threshold of 1.3 x 10(-5). The most significant loci associated with FEV1 include SNPs tagging MACROD2 (P = 6.81 x 10(-5)), CNTN5 (P = 4.37 x 10(-4)), and TRPV4 (P = 1.58 x 10(-3)). Among ever-smokers, SERPINA1 showed the most significant association with FEV1 (P = 8.41 x 10(-5)), followed by PDE4D (P = 1.22 x 10(-4)). The strongest association with FEV1/FVC ratio was observed with ABCC1 (P = 4.38 x 10(-4)), and ESR1 (P = 5.42 x 10(-4)) among ever-smokers. Conclusions: Polymorphisms spanning previously associated lung function genes did not show strong evidence for association with lung function measures in the SpiroMeta consortium population. Common SERPINA1 polymorphisms may affect FEV1 among smokers in the general population.
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4.
  • Ried, Janina S., et al. (författare)
  • A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape
  • 2016
  • Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7
  • Tidskriftsartikel (refereegranskat)abstract
    • Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways.
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5.
  • Yang, Jian, et al. (författare)
  • FTO genotype is associated with phenotypic variability of body mass index
  • 2012
  • Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 490:7419, s. 267-272
  • Tidskriftsartikel (refereegranskat)abstract
    • There is evidence across several species for genetic control of phenotypic variation of complex traits(1-4), such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using similar to 170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype)(5-7), is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of similar to 0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI8, possibly mediated by DNA methylation(9,10). Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.
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