Radiology - Research Publications

Permanent URI for this collection

http://hdl.handle.net/11343/196

Filters

2011 - 2012 2
2
Reset filters

Settings
Statistics
Citations
Author: Bahlo, Melanie × Author: JENSEN, CATHY × End date: 2012 ×

Search Results

Now showing 1 - 2 of 2
  • Item
    Thumbnail Image
    Closing the case of APOE in multiple sclerosis: no association with disease risk in over 29 000 subjects
    Lill, CM ; Liu, T ; Schjeide, B-MM ; Roehr, JT ; Akkad, DA ; Damotte, V ; Alcina, A ; Ortiz, MA ; Arroyo, R ; Lopez de lapuente, A ; Blaschke, P ; Winkelmann, A ; Gerdes, L-A ; Luessi, F ; Fernadez, O ; Izquierdo, G ; Antigueedad, A ; Hoffjan, S ; Cournu-Rebeix, I ; Gromoeller, S ; Faber, H ; Liebsch, M ; Meissner, E ; Chanvillard, C ; Touze, E ; Pico, F ; Corcia, P ; Doerner, T ; Steinhagen-Thiessen, E ; Baeckman, L ; Heekeren, HR ; Li, S-C ; Lindenberger, U ; Chan, A ; Hartung, H-P ; Aktas, O ; Lohse, P ; Kuempfel, T ; Kubisch, C ; Epplen, JT ; Zettl, UK ; Fontaine, B ; Vandenbroeck, K ; Matesanz, F ; Urcelay, E ; Bertram, L ; Zipp, F (BMJ PUBLISHING GROUP, 2012-09)
    BACKGROUND: Single nucleotide polymorphisms (SNPs) rs429358 (ε4) and rs7412 (ε2), both invoking changes in the amino-acid sequence of the apolipoprotein E (APOE) gene, have previously been tested for association with multiple sclerosis (MS) risk. However, none of these studies was sufficiently powered to detect modest effect sizes at acceptable type-I error rates. As both SNPs are only imperfectly captured on commonly used microarray genotyping platforms, their evaluation in the context of genome-wide association studies has been hindered until recently. METHODS: We genotyped 12 740 subjects hitherto not studied for their APOE status, imputed raw genotype data from 8739 subjects from five independent genome-wide association studies datasets using the most recent high-resolution reference panels, and extracted genotype data for 8265 subjects from previous candidate gene assessments. RESULTS: Despite sufficient power to detect associations at genome-wide significance thresholds across a range of ORs, our analyses did not support a role of rs429358 or rs7412 on MS susceptibility. This included meta-analyses of the combined data across 13 913 MS cases and 15 831 controls (OR=0.95, p=0.259, and OR 1.07, p=0.0569, for rs429358 and rs7412, respectively). CONCLUSION: Given the large sample size of our analyses, it is unlikely that the two APOE missense SNPs studied here exert any relevant effects on MS susceptibility.
  • Item
    Thumbnail Image
    Comparing genotyping algorithms for Illumina's Infinium whole-genome SNP BeadChips
    Ritchie, ME ; Liu, R ; Carvalho, BS ; Irizarry, RA (BMC, 2011-03-08)
    BACKGROUND: Illumina's Infinium SNP BeadChips are extensively used in both small and large-scale genetic studies. A fundamental step in any analysis is the processing of raw allele A and allele B intensities from each SNP into genotype calls (AA, AB, BB). Various algorithms which make use of different statistical models are available for this task. We compare four methods (GenCall, Illuminus, GenoSNP and CRLMM) on data where the true genotypes are known in advance and data from a recently published genome-wide association study. RESULTS: In general, differences in accuracy are relatively small between the methods evaluated, although CRLMM and GenoSNP were found to consistently outperform GenCall. The performance of Illuminus is heavily dependent on sample size, with lower no call rates and improved accuracy as the number of samples available increases. For X chromosome SNPs, methods with sex-dependent models (Illuminus, CRLMM) perform better than methods which ignore gender information (GenCall, GenoSNP). We observe that CRLMM and GenoSNP are more accurate at calling SNPs with low minor allele frequency than GenCall or Illuminus. The sample quality metrics from each of the four methods were found to have a high level of agreement at flagging samples with unusual signal characteristics. CONCLUSIONS: CRLMM, GenoSNP and GenCall can be applied with confidence in studies of any size, as their performance was shown to be invariant to the number of samples available. Illuminus on the other hand requires a larger number of samples to achieve comparable levels of accuracy and its use in smaller studies (50 or fewer individuals) is not recommended.