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Träfflista för sökning "WFRF:(Hayward Caroline) ;pers:(Langenberg Claudia);pers:(Liu Yongmei)"

Search: WFRF:(Hayward Caroline) > Langenberg Claudia > Liu Yongmei

  • Result 1-10 of 17
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1.
  • Kilpeläinen, Tuomas O, et al. (author)
  • Genetic variation near IRS1 associates with reduced adiposity and an impaired metabolic profile.
  • 2011
  • In: Nature genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 43:8, s. 753-60
  • Journal article (peer-reviewed)abstract
    • Genome-wide association studies have identified 32 loci influencing body mass index, but this measure does not distinguish lean from fat mass. To identify adiposity loci, we meta-analyzed associations between ∼2.5 million SNPs and body fat percentage from 36,626 individuals and followed up the 14 most significant (P < 10(-6)) independent loci in 39,576 individuals. We confirmed a previously established adiposity locus in FTO (P = 3 × 10(-26)) and identified two new loci associated with body fat percentage, one near IRS1 (P = 4 × 10(-11)) and one near SPRY2 (P = 3 × 10(-8)). Both loci contain genes with potential links to adipocyte physiology. Notably, the body-fat-decreasing allele near IRS1 is associated with decreased IRS1 expression and with an impaired metabolic profile, including an increased visceral to subcutaneous fat ratio, insulin resistance, dyslipidemia, risk of diabetes and coronary artery disease and decreased adiponectin levels. Our findings provide new insights into adiposity and insulin resistance.
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2.
  • Locke, Adam E, et al. (author)
  • Genetic studies of body mass index yield new insights for obesity biology.
  • 2015
  • In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 518:7538, s. 197-401
  • Journal article (peer-reviewed)abstract
    • Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.
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3.
  • Lu, Yingchang, et al. (author)
  • New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk
  • 2016
  • In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7
  • Journal article (peer-reviewed)abstract
    • To increase our understanding of the genetic basis of adiposity and its links to cardiometabolic disease risk, we conducted a genome-wide association meta-analysis of body fat percentage (BF%) in up to 100,716 individuals. Twelve loci reached genome-wide significance (P<5 × 10(-8)), of which eight were previously associated with increased overall adiposity (BMI, BF%) and four (in or near COBLL1/GRB14, IGF2BP1, PLA2G6, CRTC1) were novel associations with BF%. Seven loci showed a larger effect on BF% than on BMI, suggestive of a primary association with adiposity, while five loci showed larger effects on BMI than on BF%, suggesting association with both fat and lean mass. In particular, the loci more strongly associated with BF% showed distinct cross-phenotype association signatures with a range of cardiometabolic traits revealing new insights in the link between adiposity and disease risk.
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4.
  • Shungin, Dmitry, et al. (author)
  • New genetic loci link adipose and insulin biology to body fat distribution.
  • 2015
  • In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 518:7538, s. 187-378
  • Journal article (peer-reviewed)abstract
    • Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.
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5.
  • de Vries, Paul S., et al. (author)
  • Multiancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions
  • 2019
  • In: American Journal of Epidemiology. - : Oxford University Press. - 0002-9262 .- 1476-6256. ; 188:6, s. 1033-1054
  • Journal article (peer-reviewed)abstract
    • A person's lipid profile is influenced by genetic variants and alcohol consumption, but the contribution of interactions between these exposures has not been studied. We therefore incorporated gene-alcohol interactions into a multiancestry genome-wide association study of levels of high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. We included 45 studies in stage 1 (genome-wide discovery) and 66 studies in stage 2 (focused follow-up), for a total of 394,584 individuals from 5 ancestry groups. Analyses covered the period July 2014-November 2017. Genetic main effects and interaction effects were jointly assessed by means of a 2-degrees-of-freedom (df) test, and a 1-df test was used to assess the interaction effects alone. Variants at 495 loci were at least suggestively associated (P < 1 x 10(-6)) with lipid levels in stage 1 and were evaluated in stage 2, followed by combined analyses of stage 1 and stage 2. In the combined analysis of stages 1 and 2, a total of 147 independent loci were associated with lipid levels at P < 5 x 10(-8) using 2-df tests, of which 18 were novel. No genome-wide-significant associations were found testing the interaction effect alone. The novel loci included several genes (proprotein convertase subtilisin/kexin type 5 (PCSK5), vascular endothelial growth factor B (VEGFB), and apolipoprotein B mRNA editing enzyme, catalytic polypeptide 1 (APOBEC1) complementation factor (A1CF)) that have a putative role in lipid metabolism on the basis of existing evidence from cellular and experimental models.
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6.
  • Evangelou, Evangelos, et al. (author)
  • Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits.
  • 2018
  • In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 50:10, s. 1412-1425
  • Journal article (peer-reviewed)abstract
    • High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.
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7.
  • Feitosa, Mary F., et al. (author)
  • Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries
  • 2018
  • In: PLOS ONE. - : Public library science. - 1932-6203. ; 13:6
  • Journal article (peer-reviewed)abstract
    • Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in approximate to 131 K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P <1.0 x 10(-5)). In Stage 2, these SNVs were tested for independent external replication in individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10(-8)). For African ancestry samples, we detected 18 potentially novel BP loci (P< 5.0 x 10(-8)) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2 have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.
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8.
  • Kraja, Aldi T., et al. (author)
  • New Blood Pressure-Associated Loci Identified in Meta-Analyses of 475000 Individuals
  • 2017
  • In: Circulation. - : LIPPINCOTT WILLIAMS & WILKINS. - 1942-325X .- 1942-3268. ; 10:5
  • Journal article (peer-reviewed)abstract
    • Background - Genome-wide association studies have recently identified >400 loci that harbor DNA sequence variants that influence blood pressure (BP). Our earlier studies identified and validated 56 single nucleotide variants (SNVs) associated with BP from meta-analyses of exome chip genotype data. An additional 100 variants yielded suggestive evidence of association.Methods and Results - Here, we augment the sample with 140886 European individuals from the UK Biobank, in whom 77 of the 100 suggestive SNVs were available for association analysis with systolic BP or diastolic BP or pulse pressure. We performed 2 meta-analyses, one in individuals of European, South Asian, African, and Hispanic descent (pan-ancestry, approximate to 475000), and the other in the subset of individuals of European descent (approximate to 423000). Twenty-one SNVs were genome-wide significant (P<5x10(-8) ) for BP, of which 4 are new BP loci: rs9678851 (missense, SLC4A1AP), rs7437940 (AFAP1), rs13303 (missense, STAB1), and rs1055144 (7p15.2). In addition, we identified a potentially independent novel BP-associated SNV, rs3416322 (missense, SYNPO2L) at a known locus, uncorrelated with the previously reported SNVs. Two SNVs are associated with expression levels of nearby genes, and SNVs at 3 loci are associated with other traits. One SNV with a minor allele frequency <0.01, (rs3025380 at DBH) was genome-wide significant.Conclusions - We report 4 novel loci associated with BP regulation, and 1 independent variant at an established BP locus. This analysis highlights several candidate genes with variation that alter protein function or gene expression for potential follow-up.
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9.
  • Lagou, Vasiliki, et al. (author)
  • Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability
  • 2021
  • In: Nature Communications. - : Nature Publishing Group. - 2041-1723. ; 12:1
  • Journal article (peer-reviewed)abstract
    • Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.
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10.
  • Mahajan, Anubha, et al. (author)
  • Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes
  • 2018
  • In: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 50:4, s. 559-571
  • Journal article (peer-reviewed)abstract
    • We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10−7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent ‘false leads’ with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.
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  • Result 1-10 of 17
Type of publication
journal article (17)
Type of content
peer-reviewed (17)
Author/Editor
Wareham, Nicholas J. (17)
Hayward, Caroline (17)
Laakso, Markku (16)
Boehnke, Michael (16)
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Harris, Tamara B (16)
Gudnason, Vilmundur (16)
Rudan, Igor (15)
Loos, Ruth J F (15)
Kuusisto, Johanna (14)
van Duijn, Cornelia ... (14)
Scott, Robert A (14)
Uitterlinden, André ... (14)
Ridker, Paul M. (13)
Chasman, Daniel I. (13)
Luan, Jian'an (13)
Esko, Tõnu (13)
Jackson, Anne U. (13)
Salomaa, Veikko (12)
Amin, Najaf (12)
Gieger, Christian (12)
Peters, Annette (12)
Mahajan, Anubha (12)
Munroe, Patricia B. (12)
Polasek, Ozren (12)
Perola, Markus (11)
Lind, Lars (11)
Deloukas, Panos (11)
McCarthy, Mark I (11)
Mohlke, Karen L (11)
Tuomilehto, Jaakko (11)
Rotter, Jerome I. (11)
Metspalu, Andres (11)
Palmer, Colin N. A. (11)
Franco, Oscar H. (11)
Boerwinkle, Eric (11)
Watkins, Hugh (11)
Goel, Anuj (11)
Rauramaa, Rainer (11)
Raitakari, Olli T (10)
Franks, Paul W. (10)
Stancáková, Alena (10)
Samani, Nilesh J. (10)
Froguel, Philippe (10)
Zhao, Jing Hua (10)
Hofman, Albert (10)
Psaty, Bruce M (10)
van der Harst, Pim (10)
Lakka, Timo A (10)
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University
Lund University (15)
Uppsala University (14)
Umeå University (13)
Karolinska Institutet (13)
University of Gothenburg (4)
Stockholm University (3)
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Language
English (17)
Research subject (UKÄ/SCB)
Medical and Health Sciences (17)
Natural sciences (6)

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