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Sökning: WFRF:(Völker Uwe) > (2007-2009)

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  • Kolz, Melanie, et al. (författare)
  • Meta-analysis of 28,141 individuals identifies common variants within five new loci that influence uric acid concentrations
  • 2009
  • Ingår i: PLoS genetics. - 1553-7404. ; 5:6, s. e1000504-
  • Tidskriftsartikel (refereegranskat)abstract
    • Elevated serum uric acid levels cause gout and are a risk factor for cardiovascular disease and diabetes. To investigate the polygenetic basis of serum uric acid levels, we conducted a meta-analysis of genome-wide association scans from 14 studies totalling 28,141 participants of European descent, resulting in identification of 954 SNPs distributed across nine loci that exceeded the threshold of genome-wide significance, five of which are novel. Overall, the common variants associated with serum uric acid levels fall in the following nine regions: SLC2A9 (p = 5.2×10−201), ABCG2 (p = 3.1×10−26), SLC17A1 (p = 3.0×10−14), SLC22A11 (p = 6.7×10−14), SLC22A12 (p = 2.0×10−9), SLC16A9 (p = 1.1×10−8), GCKR (p = 1.4×10−9), LRRC16A (p = 8.5×10−9), and near PDZK1 (p = 2.7×10−9). Identified variants were analyzed for gender differences. We found that the minor allele for rs734553 in SLC2A9 has greater influence in lowering uric acid levels in women and the minor allele of rs2231142 in ABCG2 elevates uric acid levels more strongly in men compared to women. To further characterize the identified variants, we analyzed their association with a panel of metabolites. rs12356193 within SLC16A9 was associated with DL-carnitine (p = 4.0×10−26) and propionyl-L-carnitine (p = 5.0×10−8) concentrations, which in turn were associated with serum UA levels (p = 1.4×10−57 and p = 8.1×10−54, respectively), forming a triangle between SNP, metabolites, and UA levels. Taken together, these associations highlight additional pathways that are important in the regulation of serum uric acid levels and point toward novel potential targets for pharmacological intervention to prevent or treat hyperuricemia. In addition, these findings strongly support the hypothesis that transport proteins are key in regulating serum uric acid levels.
  • Thiele, Thomas, et al. (författare)
  • Profiling of alterations in platelet proteins during storage of platelet concentrates.
  • 2007
  • Ingår i: Transfusion. - 0041-1132 .- 1537-2995. ; 47:7, s. 1221-33
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: The quality of platelet concentrates (PCs) is primarily determined in vitro by selective methods (e.g., pH, aggregometry), which provide only limited information on certain platelet (PLT) characteristics. In contrast, proteomic technologies provide a comprehensive overview of the PLT proteome. High interassay variability, however, limits meaningful assessment of samples taken from the same product over time or before and after processing. STUDY DESIGN AND METHODS: Differential in-gel electrophoresis (DIGE) and mass spectrometry were applied to analyze changes in the PLT proteome during storage of PCs. RESULTS: DIGE provides a comprehensive and reproducible overview of the cytoplasmic PLT proteome (median standard deviation of protein spot intensities, 5%-9%). Although 97 percent of cytosolic PLT proteins remained unchanged over a 9-day storage period, septin 2 showed characteristic alterations that preceded by several days more widespread alterations affecting numerous other proteins. Also beta-actin and gelsolin are potential marker proteins for changes in the PLT proteome. Interestingly septin 2 and gelsolin are affected during apoptosis, indicating that apoptosis in PCs may have an impact on PLT storage. CONCLUSION: DIGE is a tool for comprehensively assessing the impact of storage on the global proteome profile of therapeutic PCs. Most of the changes detected are in high-abundance PLT proteins.
  • Vasan, Ramachandran S, et al. (författare)
  • Genetic variants associated with cardiac structure and function : a meta-analysis and replication of genome-wide association data
  • 2009
  • Ingår i: Journal of the American Medical Association (JAMA). - 0098-7484 .- 1538-3598. ; 302:2, s. 168-178
  • Tidskriftsartikel (refereegranskat)abstract
    • CONTEXT: Echocardiographic measures of left ventricular (LV) structure and function are heritable phenotypes of cardiovascular disease. OBJECTIVE: To identify common genetic variants associated with cardiac structure and function by conducting a meta-analysis of genome-wide association data in 5 population-based cohort studies (stage 1) with replication (stage 2) in 2 other community-based samples. DESIGN, SETTING, AND PARTICIPANTS: Within each of 5 community-based cohorts comprising the EchoGen consortium (stage 1; n = 12 612 individuals of European ancestry; 55% women, aged 26-95 years; examinations between 1978-2008), we estimated the association between approximately 2.5 million single-nucleotide polymorphisms (SNPs; imputed to the HapMap CEU panel) and echocardiographic traits. In stage 2, SNPs significantly associated with traits in stage 1 were tested for association in 2 other cohorts (n = 4094 people of European ancestry). Using a prespecified P value threshold of 5 x 10(-7) to indicate genome-wide significance, we performed an inverse variance-weighted fixed-effects meta-analysis of genome-wide association data from each cohort. MAIN OUTCOME MEASURES: Echocardiographic traits: LV mass, internal dimensions, wall thickness, systolic dysfunction, aortic root, and left atrial size. RESULTS: In stage 1, 16 genetic loci were associated with 5 echocardiographic traits: 1 each with LV internal dimensions and systolic dysfunction, 3 each with LV mass and wall thickness, and 8 with aortic root size. In stage 2, 5 loci replicated (6q22 locus associated with LV diastolic dimensions, explaining <1% of trait variance; 5q23, 12p12, 12q14, and 17p13 associated with aortic root size, explaining 1%-3% of trait variance). CONCLUSIONS: We identified 5 genetic loci harboring common variants that were associated with variation in LV diastolic dimensions and aortic root size, but such findings explained a very small proportion of variance. Further studies are required to replicate these findings, identify the causal variants at or near these loci, characterize their functional significance, and determine whether they are related to overt cardiovascular disease.
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