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| 2. |
- Koettgen, Anna, et al.
(författare)
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Genome-wide association analyses identify 18 new loci associated with serum urate concentrations
- 2013
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:2, s. 145-154
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Tidskriftsartikel (refereegranskat)abstract
- Elevated serum urate concentrations can cause gout, a prevalent and painful inflammatory arthritis. By combining data from >140,000 individuals of European ancestry within the Global Urate Genetics Consortium (GUGC), we identified and replicated 28 genome-wide significant loci in association with serum urate concentrations (18 new regions in or near TRIM46, INHBB, SEMBT1, TMEM171, VEGFA, BAZ1B, PRKAG2, STC1, HNF4G, A1CF, ATXN2, UBE2Q2, IGF1R, NFAT5, MAF, HLF, ACVR1B-ACVRL1 and B3GNT4). Associations for many of the loci were of similar magnitude in individuals of non-European ancestry. We further characterized these loci for associations with gout, transcript expression and the fractional excretion of urate. Network analyses implicate the inhibins-activins signaling pathways and glucose metabolism in systemic urate control. New candidate genes for serum urate concentration highlight the importance of metabolic control of urate production and excretion, which may have implications for the treatment and prevention of gout.
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| 3. |
- Nowicka, Paulina, 1974-, et al.
(författare)
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Utility of Hemoglobin A1c for Diagnosing Prediabetes and Diabetes in Obese Children and Adolescents
- 2011
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Ingår i: Diabetes Care. - : American Diabetes Association. - 0149-5992 .- 1935-5548. ; 34:6, s. 1306-1311
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE—Hemoglobin A1c (A1C) has emerged as a recommended diagnostic tool for identifying diabetes and subjects at risk for the disease. This recommendation is based on data in adults showing the relationship between A1C with future development of diabetes and microvascular complications. However, studies in the pediatric population are lacking.RESEARCH DESIGN AND METHODS—We studied a multiethnic cohort of 1,156 obese children and adolescents without a diagnosis of diabetes (male, 40%/female, 60%). All subjects underwent an oral glucose tolerance test (OGTT) and A1C measurement. These tests were repeated after a follow-up time of ;2 years in 218 subjects.RESULTS—At baseline, subjects were stratified according to A1C categories: 77% with normal glucose tolerance (A1C,5.7%), 21% at risk for diabetes (A1C 5.7–6.4%), and 1% with diabetes (A1C .6.5%). In the at risk for diabetes category, 47% were classified with prediabetes or diabetes, and in the diabetes category, 62% were classified with type 2 diabetes by the OGTT. The area under the curve receiver operating characteristic for A1C was 0.81 (95%CI 0.70–0.92). The threshold for identifying type 2 diabetes was 5.8%, with 78% specificity and 68% sensitivity. In the subgroup with repeated measures, a multivariate analysis showed that the strongest predictors of 2-h glucose at follow-up were baseline A1C and 2-h glucose, independently of age, ethnicity, sex, fasting glucose, and follow-up time.CONCLUSIONS—The American Diabetes Association suggested that an A1C of 6.5% underestimates the prevalence of prediabetes and diabetes in obese children and adolescents. Given the low sensitivity and specificity, the use of A1C by itself represents a poor diagnostic tool for prediabetes and type 2 diabetes in obese children and adolescents.
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| 4. |
- Thompson, Paul M., et al.
(författare)
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The ENIGMA Consortium : large-scale collaborative analyses of neuroimaging and genetic data
- 2014
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Ingår i: BRAIN IMAGING BEHAV. - : Springer Science and Business Media LLC. - 1931-7557 .- 1931-7565. ; 8:2, s. 153-182
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Tidskriftsartikel (refereegranskat)abstract
- The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.
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| 5. |
- Yang, Jian, et al.
(författare)
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FTO genotype is associated with phenotypic variability of body mass index
- 2012
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 490:7419, s. 267-272
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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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