179 results found
Flannick J, Fuchsberger C, Mahajan A, et al., 2018, Sequence data and association statistics from 12,940 type 2 diabetes cases and controls (vol 4, 170179, 2017), SCIENTIFIC DATA, Vol: 5, ISSN: 2052-4463
Flannick J, Fuchsberger C, Mahajan A, et al., 2017, Data Descriptor: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls, SCIENTIFIC DATA, Vol: 4, ISSN: 2052-4463
Graff M, Scott RA, Justice AE, et al., 2017, Genome-wide physical activity interactions in adiposity. A meta-analysis of 200,452 adults, PLOS GENETICS, Vol: 13, ISSN: 1553-7404
Graff M, Scott RA, Justice AE, et al., 2017, Correction: Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults., PLoS Genet, Vol: 13
[This corrects the article DOI: 10.1371/journal.pgen.1006528.].
Hinney A, Kesselmeier M, Jall S, et al., 2017, Evidence for three genetic loci involved in both anorexia nervosa risk and variation of body mass index, MOLECULAR PSYCHIATRY, Vol: 22, Pages: 192-201, ISSN: 1359-4184
Kaakinen M, Magi R, Fischer K, et al., 2017, MARV: a tool for genome-wide multi-phenotype analysis of rare variants, BMC BIOINFORMATICS, Vol: 18, ISSN: 1471-2105
Magi R, Suleimanov YV, Clarke GM, et al., 2017, SCOPA and META-SCOPA: software for the analysis and aggregation of genome-wide association studies of multiple correlated phenotypes, BMC BIOINFORMATICS, Vol: 18, ISSN: 1471-2105
Manning A, Highland HM, Gasser J, et al., 2017, A Low-Frequency Inactivating AKT2 Variant Enriched in the Finnish Population Is Associated With Fasting Insulin Levels and Type 2 Diabetes Risk, DIABETES, Vol: 66, Pages: 2019-2032, ISSN: 0012-1797
Pervjakova N, Prokopenko I, 2017, The TAD-pathway for GWAS signals, EUROPEAN JOURNAL OF HUMAN GENETICS, Vol: 25, Pages: 1179-1180, ISSN: 1018-4813
Scott RA, Scott LJ, Maegi R, et al., 2017, An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans, DIABETES, Vol: 66, Pages: 2888-2902, ISSN: 0012-1797
Teumer A, Qi Q, Nethander M, et al., 2017, Genomewide meta-analysis identifies loci associated with IGF-I and IGEBP-3 levels with impact on age-related traits (vol 15, pg 811, 2016), AGING CELL, Vol: 16, Pages: 898-898, ISSN: 1474-9726
Wheeler E, Leong A, Liu C-T, et al., 2017, Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations: A transethnic genome-wide meta-analysis, PLOS MEDICINE, Vol: 14, ISSN: 1549-1676
Anasanti MD, Kaakinen M, Jarvelin M-R, et al., 2016, Modern Approaches to Address Missing Data in Multi-Phenotype Genome-Wide Association Studies, 45th European Mathematical Genetics Meeting (EMGM), Publisher: KARGER, Pages: 229-229, ISSN: 0001-5652
Barban N, Jansen R, de Vlaming R, et al., 2016, Genome-wide analysis identifies 12 loci influencing human reproductive behavior, NATURE GENETICS, Vol: 48, Pages: 1462-1472, ISSN: 1061-4036
Bodea CA, Neale BM, Ripke S, et al., 2016, A Method to Exploit the Structure of Genetic Ancestry Space to Enhance Case-Control Studies, AMERICAN JOURNAL OF HUMAN GENETICS, Vol: 98, Pages: 857-868, ISSN: 0002-9297
Horikoshi M, Beaumont RN, Day FR, et al., 2016, Genome-wide associations for birth weight and correlations with adult disease, Nature, Vol: 538, Pages: 248-252, ISSN: 0028-0836
Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW (P < 5 × 10(-8)). Overall, approximately 15% of variance in BW was captured by assays of fetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure (Rg = -0.22, P = 5.5 × 10(-13)), T2D (Rg = -0.27, P = 1.1 × 10(-6)) and coronary artery disease (Rg = -0.30, P = 6.5 × 10(-9)). In addition, using large -cohort datasets, we demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions (P = 1.9 × 10(-4)). We demonstrate that life-course associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and identify some of the pathways through which these causal genetic effects are mediated.
Kaakinen M, Lagou V, Magie R, et al., 2016, Multi-Phenotype Genome-Wide Meta-Analysis of Lipid Levels and BMI in 64,736 Europeans Suggests Shared Genetic Architecture, 45th European Mathematical Genetics Meeting (EMGM), Publisher: KARGER, Pages: 213-213, ISSN: 0001-5652
Lindqvist D, Prokopenko I, Londos E, et al., 2016, Associations between TOMM40 Poly-T Repeat Variants and Dementia in Cases with Parkinsonism, JOURNAL OF PARKINSONS DISEASE, Vol: 6, Pages: 99-108, ISSN: 1877-7171
Lu Y, Day FR, Gustafsson S, et al., 2016, New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk, NATURE COMMUNICATIONS, Vol: 7, ISSN: 2041-1723
Pattaro C, Teumer A, Gorski M, et al., 2016, Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function, NATURE COMMUNICATIONS, Vol: 7, ISSN: 2041-1723
Ried JS, Jeff JM, Chu AY, et al., 2016, A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape, NATURE COMMUNICATIONS, Vol: 7, ISSN: 2041-1723
Spjuth O, Krestyaninova M, Hastings J, et al., 2016, Harmonising and linking biomedical and clinical data across disparate data archives to enable integrative cross-biobank research, EUROPEAN JOURNAL OF HUMAN GENETICS, Vol: 24, Pages: 521-528, ISSN: 1018-4813
Teumer A, Qi Q, Nethander M, et al., 2016, Genomewide meta-analysis identifies loci associated with IGF-I and IGFBP-3 levels with impact on age-related traits, AGING CELL, Vol: 15, Pages: 811-824, ISSN: 1474-9718
Urich A, Kaakinen M, Jiang L, et al., 2016, An Investigation into the Nutrigenomics of Pancreatic Cancer Using Data from the EPIC Study, 45th European Mathematical Genetics Meeting (EMGM), Publisher: KARGER, Pages: 227-228, ISSN: 0001-5652
Walford GA, Gustafsson S, Rybin D, et al., 2016, Genome-wide association study of the modified Stumvoll Insulin Sensitivity Index identifies BCL2 and FAM19A2 as novel insulin sensitivity loci, Diabetes, Vol: 65, Pages: 3200-3211, ISSN: 0012-1797
Genome-wide association studies (GWAS) have found few common variants that influence fasting measures of insulin sensitivity. We hypothesized that a GWAS of an integrated assessment of fasting and dynamic measures of insulin sensitivity would detect novel common variants. We performed GWAS of the modified Stumvoll Insulin Sensitivity Index (ISI) within the Meta-Analyses of Glucose and Insulin-related traits Consortium. Discovery was performed in 16,753 individuals, and replication was attempted for the 23 most significant novel loci in 13,354 independent individuals. Association with ISI was tested in models adjusted for age, sex, body mass index (BMI) and in a model ("Model 3") analyzing the combined influence of the genotype effect adjusted for BMI and the interaction effect between the genotype and BMI on ISI. In Model 3, three variants reached genome-wide significance: rs13422522 (NYAP2, P=8.87 ×10(-11)), rs12454712 (BCL2, P=2.7×10(-8)) and rs10506418 (FAM19A2, P=1.9×10(-8)). The association at NYAP2 was eliminated by conditioning on the known IRS1 insulin sensitivity locus; the BCL2 and FAM19A2 associations were independent of known cardio-metabolic loci. In conclusion, we identified two novel loci and replicated known variants associated with insulin sensitivity. Further studies are needed to clarify the causal variant and function at the BCL2 and FAM19A2 loci.
Winkler TW, Justice AE, Graff M, et al., 2016, Correction: The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study, PLOS Genetics, Vol: 12, Pages: e1006166-e1006166, ISSN: 1553-7390
Cornelis MC, Byrne EM, Esko T, et al., 2015, Genome-wide meta-analysis identifies six novel loci associated with habitual coffee consumption, MOLECULAR PSYCHIATRY, Vol: 20, Pages: 647-656, ISSN: 1359-4184
De T, Prokopenko I, Jarvelin M-R, et al., 2015, Metabonomic Signatures of CNVs in TSPAN8 Exonic Regions Associated with Type 2 Diabetes, 43rd European Mathematical Genetics Meeting (EMGM), Publisher: KARGER, Pages: 33-33, ISSN: 0001-5652
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