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- Prokopenko, Inga, et al.
(författare)
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Variants in MTNR1B influence fasting glucose levels
- 2009
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 41:1, s. 77-81
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Tidskriftsartikel (refereegranskat)abstract
- To identify previously unknown genetic loci associated with fasting glucose concentrations, we examined the leading association signals in ten genome-wide association scans involving a total of 36,610 individuals of European descent. Variants in the gene encoding melatonin receptor 1B (MTNR1B) were consistently associated with fasting glucose across all ten studies. The strongest signal was observed at rs10830963, where each G allele (frequency 0.30 in HapMap CEU) was associated with an increase of 0.07 (95% CI = 0.06-0.08) mmol/l in fasting glucose levels (P = 3.2 x 10(-50)) and reduced beta-cell function as measured by homeostasis model assessment (HOMA-B, P = 1.1 x 10(-15)). The same allele was associated with an increased risk of type 2 diabetes (odds ratio = 1.09 (1.05-1.12), per G allele P = 3.3 x 10(-7)) in a meta-analysis of 13 case-control studies totaling 18,236 cases and 64,453 controls. Our analyses also confirm previous associations of fasting glucose with variants at the G6PC2 (rs560887, P = 1.1 x 10(-57)) and GCK (rs4607517, P = 1.0 x 10(-25)) loci.
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| 2. |
- Bakaysa, S.L., et al.
(författare)
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Telomere length predicts survival independent of genetic influences
- 2007
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Ingår i: Aging Cell. ; 63:6, s. 769-774
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Tidskriftsartikel (refereegranskat)abstract
- Telomeres prevent the loss of coding genetic material during chromosomal replication. Previous research suggests that shorter telomere length may be associated with lower survival. Because genetic factors are important for individual differences in both telomere length and mortality, this association could reflect genetic or environmental pleiotropy rather than a direct biological effect of telomeres. We demonstrate through within-pair analyses of Swedish twins that telomere length at advanced age is a biomarker that predicts survival beyond the impact of early familial environment and genetic factors in common with telomere length and mortality. Twins with the shortest telomeres had a three times greater risk of death during the follow-up period than their co-twins with the longest telomere measurements [hazard ratio (RR) = 2.8, 95% confidence interval 1.1-7.3, P = 0.03].
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| 5. |
- Lundmark, Per E, et al.
(författare)
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Evaluation of HapMap data in six populations of European descent
- 2008
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Ingår i: European Journal of Human Genetics. - : Springer Science and Business Media LLC. - 1018-4813 .- 1476-5438. ; 16:9, s. 1142-1150
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Tidskriftsartikel (refereegranskat)abstract
- We studied how well the European CEU samples used in the Haplotype Mapping Project (HapMap) represent five European populations by analyzing nuclear family samples from the Swedish, Finnish, Dutch, British and Australian (European ancestry) populations. The number of samples from each population (about 30 parent-offspring trios) was similar to that in the HapMap sample sets. A panel of 186 single nucleotide polymorphisms (SNPs) distributed over the 1.5 Mb region of the GRID2 gene on chromosome 4 was genotyped. The genotype data were compared pair-wise between the HapMap sample and the other population samples. Principal component analysis (PCA) was used to cluster the data from different populations with respect to allele frequencies and to define the markers responsible for observed variance. The only sample with detectable differences in allele frequencies was that from Kuusamo, Finland. This sample also separated from the others, including the other Finnish sample, in the PCA analysis. A set of tagSNPs was defined based on the HapMap data and applied to the samples. The tagSNPs were found to capture the genetic variation in the analyzed region at r(2)>0.8 at levels ranging from 95% in the Kuusamo sample to 87% in the Australian sample. To capture the maximal genetic variation in the region, the Kuusamo, HapMap and Australian samples required 58, 63 and 73 native tagSNPs, respectively. The HapMap CEU sample represents the European samples well for tagSNP selection, with some caution regarding estimation of allele frequencies in the Finnish Kuusamo sample, and a slight reduction in tagging efficiency in the Australian sample.
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| 6. |
- McEvoy, Brian P., et al.
(författare)
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Geographical structure and differential natural selection among North European populations
- 2009
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Ingår i: Genome Research. - : Cold Spring Harbor Laboratory. - 1088-9051 .- 1549-5469. ; 19:5, s. 804-814
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Tidskriftsartikel (refereegranskat)abstract
- Population structure can provide novel insight into the human past, and recognizing and correcting for such stratification is a practical concern in gene mapping by many association methodologies. We investigate these patterns, primarily through principal component (PC) analysis of whole genome SNP polymorphism, in 2099 individuals from populations of Northern European origin (Ireland, United Kingdom, Netherlands, Denmark, Sweden, Finland, Australia, and HapMap European-American). The major trends (PC1 and PC2) demonstrate an ability to detect geographic substructure, even over a small area like the British Isles, and this information can then be applied to finely dissect the ancestry of the European-Australian and European-American samples. They simultaneously point to the importance of considering population stratification in what might be considered a small homogeneous region. There is evidence from FST-based analysis of genic and nongenic SNPs that differential positive selection has operated across these populations despite their short divergence time and relatively similar geographic and environmental range. The pressure appears to have been focused on genes involved in immunity, perhaps reflecting response to infectious disease epidemic. Such an event may explain a striking selective sweep centered on the rs2508049-G allele, close to the HLA-G gene on chromosome 6. Evidence of the sweep extends over a 8-Mb/3.5-cM region. Overall, the results illustrate the power of dense genotype and sample data to explore regional population variation, the events that have crafted it, and their implications in both explaining disease prevalence and mapping these genes by association.
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