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Sökning: WFRF:(Barroso Ines)

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1.
  • Ali, Ashfaq, et al. (författare)
  • Do Genetic Factors Modify the Relationship Between Obesity and Hypertriglyceridemia? : Findings From the GLACIER and the MDC Studies
  • 2016
  • Ingår i: Circulation. - 1942-325X .- 1942-3268. ; 9:2, s. 162-171
  • Tidskriftsartikel (refereegranskat)abstract
    • Background Obesity is a major risk factor for dyslipidemia, but this relationship is highly variable. Recently published data from 2 Danish cohorts suggest that genetic factors may underlie some of this variability.Methods and Results We tested whether established triglyceride-associated loci modify the relationship of body mass index (BMI) and triglyceride concentrations in 2 Swedish cohorts (the Gene-Lifestyle Interactions and Complex Traits Involved in Elevated Disease Risk [GLACIER Study; N=4312] and the Malmo Diet and Cancer Study [N=5352]). The genetic loci were amalgamated into a weighted genetic risk score (WGRS(TG)) by summing the triglyceride-elevating alleles (weighted by their established marginal effects) for all loci. Both BMI and the WGRS(TG) were strongly associated with triglyceride concentrations in GLACIER, with each additional BMI unit (kg/m(2)) associated with 2.8% (P=8.4x10(-84)) higher triglyceride concentration and each additional WGRS(TG) unit with 2% (P=7.6x10(-48)) higher triglyceride concentration. Each unit of the WGRS(TG) was associated with 1.5% higher triglyceride concentrations in normal weight and 2.4% higher concentrations in overweight/obese participants (P-interaction=0.056). Meta-analyses of results from the Swedish cohorts yielded a statistically significant WGRS(TG)xBMI interaction effect (P-interaction=6.0x10(-4)), which was strengthened by including data from the Danish cohorts (P-interaction=6.5x10(-7)). In the meta-analysis of the Swedish cohorts, nominal evidence of a 3-way interaction (WGRS(TG)xBMIxsex) was observed (P-interaction=0.03), where the WGRS(TG)xBMI interaction was only statistically significant in females. Using protein-protein interaction network analyses, we identified molecular interactions and pathways elucidating the metabolic relationships between BMI and triglyceride-associated loci.Conclusions Our findings provide evidence that body fatness accentuates the effects of genetic susceptibility variants in hypertriglyceridemia, effects that are most evident in females.
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2.
  • Artigas Soler, María, et al. (författare)
  • Genome-wide association and large-scale follow up identifies 16 new loci influencing lung function.
  • 2011
  • Ingår i: Nature genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 43:11, s. 1082-90
  • Tidskriftsartikel (refereegranskat)abstract
    • Pulmonary function measures reflect respiratory health and are used in the diagnosis of chronic obstructive pulmonary disease. We tested genome-wide association with forced expiratory volume in 1 second and the ratio of forced expiratory volume in 1 second to forced vital capacity in 48,201 individuals of European ancestry with follow up of the top associations in up to an additional 46,411 individuals. We identified new regions showing association (combined P < 5 × 10(-8)) with pulmonary function in or near MFAP2, TGFB2, HDAC4, RARB, MECOM (also known as EVI1), SPATA9, ARMC2, NCR3, ZKSCAN3, CDC123, C10orf11, LRP1, CCDC38, MMP15, CFDP1 and KCNE2. Identification of these 16 new loci may provide insight into the molecular mechanisms regulating pulmonary function and into molecular targets for future therapy to alleviate reduced lung function.
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4.
  • Auffray, Charles, et al. (författare)
  • Making sense of big data in health research: Towards an EU action plan
  • 2016
  • Ingår i: Genome Medicine. - : BIOMED CENTRAL LTD. - 1756-994X .- 1756-994X. ; 8:71
  • Tidskriftsartikel (refereegranskat)abstract
    • Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health arid healthcare for all Europearis.
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5.
  • Berndt, Sonja I., et al. (författare)
  • Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture
  • 2013
  • Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:5, s. 501-U69
  • Tidskriftsartikel (refereegranskat)abstract
    • Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.
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6.
  • Broadaway, K Alaine, et al. (författare)
  • Loci for insulin processing and secretion provide insight into type 2 diabetes risk.
  • 2023
  • Ingår i: American Journal of Human Genetics. - : Elsevier. - 0002-9297 .- 1537-6605. ; 110:2, s. 284-299
  • Tidskriftsartikel (refereegranskat)abstract
    • Insulin secretion is critical for glucose homeostasis, and increased levels of the precursor proinsulin relative to insulin indicate pancreatic islet beta-cell stress and insufficient insulin secretory capacity in the setting of insulin resistance. We conducted meta-analyses of genome-wide association results for fasting proinsulin from 16 European-ancestry studies in 45,861 individuals. We found 36 independent signals at 30 loci (p value < 5 × 10-8), which validated 12 previously reported loci for proinsulin and ten additional loci previously identified for another glycemic trait. Half of the alleles associated with higher proinsulin showed higher rather than lower effects on glucose levels, corresponding to different mechanisms. Proinsulin loci included genes that affect prohormone convertases, beta-cell dysfunction, vesicle trafficking, beta-cell transcriptional regulation, and lysosomes/autophagy processes. We colocalized 11 proinsulin signals with islet expression quantitative trait locus (eQTL) data, suggesting candidate genes, including ARSG, WIPI1, SLC7A14, and SIX3. The NKX6-3/ANK1 proinsulin signal colocalized with a T2D signal and an adipose ANK1 eQTL signal but not the islet NKX6-3 eQTL. Signals were enriched for islet enhancers, and we showed a plausible islet regulatory mechanism for the lead signal in the MADD locus. These results show how detailed genetic studies of an intermediate phenotype can elucidate mechanisms that may predispose one to disease.
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7.
  • Brunkwall, Louise, et al. (författare)
  • Sugar-sweetened beverage consumption and genetic predisposition to obesity in 2 Swedish cohorts
  • 2016
  • Ingår i: American Journal of Clinical Nutrition. - : Elsevier BV. - 0002-9165 .- 1938-3207. ; 104:3, s. 809-815
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: The consumption of sugar-sweetened beverages (SSBs), which has increased substantially during the last decades, has been associated with obesity and weight gain.Objective: Common genetic susceptibility to obesity has been shown to modify the association between SSB intake and obesity risk in 3 prospective cohorts from the United States. We aimed to replicate these findings in 2 large Swedish cohorts.Design: Data were available for 21,824 healthy participants from the Malmö Diet and Cancer study and 4902 healthy participants from the Gene-Lifestyle Interactions and Complex Traits Involved in Elevated Disease Risk Study. Self-reported SSB intake was categorized into 4 levels (seldom, low, medium, and high). Unweighted and weighted genetic risk scores (GRSs) were constructed based on 30 body mass index [(BMI) in kg/m2]-associated loci, and effect modification was assessed in linear regression equations by modeling the product and marginal effects of the GRS and SSB intake adjusted for age-, sex-, and cohort-specific covariates, with BMI as the outcome. In a secondary analysis, models were additionally adjusted for putative confounders (total energy intake, alcohol consumption, smoking status, and physical activity).Results: In an inverse variance-weighted fixed-effects meta-analysis, each SSB intake category increment was associated with a 0.18 higher BMI (SE = 0.02; P = 1.7 × 10−20; n = 26,726). In the fully adjusted model, a nominal significant interaction between SSB intake category and the unweighted GRS was observed (P-interaction = 0.03). Comparing the participants within the top and bottom quartiles of the GRS to each increment in SSB intake was associated with 0.24 (SE = 0.04; P = 2.9 × 10−8; n = 6766) and 0.15 (SE = 0.04; P = 1.3 × 10−4; n = 6835) higher BMIs, respectively.Conclusions: The interaction observed in the Swedish cohorts is similar in magnitude to the previous analysis in US cohorts and indicates that the relation of SSB intake and BMI is stronger in people genetically predisposed to obesity.
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8.
  • Cai, Lina, et al. (författare)
  • Genome-wide association analysis of type 2 diabetes in the EPIC-InterAct study
  • 2020
  • Ingår i: Scientific Data. - : Nature Publishing Group. - 2052-4463. ; 7:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Type 2 diabetes (T2D) is a global public health challenge. Whilst the advent of genome-wide association studies has identified >400 genetic variants associated with T2D, our understanding of its biological mechanisms and translational insights is still limited. The EPIC-InterAct project, centred in 8 countries in the European Prospective Investigations into Cancer and Nutrition study, is one of the largest prospective studies of T2D. Established as a nested case-cohort study to investigate the interplay between genetic and lifestyle behavioural factors on the risk of T2D, a total of 12,403 individuals were identified as incident T2D cases, and a representative sub-cohort of 16,154 individuals was selected from a larger cohort of 340,234 participants with a follow-up time of 3.99 million person-years. We describe the results from a genome-wide association analysis between more than 8.9 million SNPs and T2D risk among 22,326 individuals (9,978 cases and 12,348 non-cases) from the EPIC-InterAct study. The summary statistics to be shared provide a valuable resource to facilitate further investigations into the genetics of T2D.
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9.
  • Craddock, Nick, et al. (författare)
  • Genome-wide association study of CNVs in 16,000 cases of eight common diseases and 3,000 shared controls
  • 2010
  • Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 464:7289, s. 713-720
  • Tidskriftsartikel (refereegranskat)abstract
    • Copy number variants (CNVs) account for a major proportion of human genetic polymorphism and have been predicted to have an important role in genetic susceptibility to common disease. To address this we undertook a large, direct genome-wide study of association between CNVs and eight common human diseases. Using a purpose-designed array we typed,19,000 individuals into distinct copy-number classes at 3,432 polymorphic CNVs, including an estimated similar to 50% of all common CNVs larger than 500 base pairs. We identified several biological artefacts that lead to false-positive associations, including systematic CNV differences between DNAs derived from blood and cell lines. Association testing and follow-up replication analyses confirmed three loci where CNVs were associated with disease-IRGM for Crohn's disease, HLA for Crohn's disease, rheumatoid arthritis and type 1 diabetes, and TSPAN8 for type 2 diabetes-although in each case the locus had previously been identified in single nucleotide polymorphism (SNP)-based studies, reflecting our observation that most common CNVs that are well-typed on our array are well tagged by SNPs and so have been indirectly explored through SNP studies. We conclude that common CNVs that can be typed on existing platforms are unlikely to contribute greatly to the genetic basis of common human diseases.
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10.
  • Dimas, Antigone S, et al. (författare)
  • Impact of type 2 diabetes susceptibility variants on quantitative glycemic traits reveals mechanistic heterogeneity.
  • 2014
  • Ingår i: Diabetes. - : American Diabetes Association. - 1939-327X .- 0012-1797. ; 63:6, s. 2158-2171
  • Tidskriftsartikel (refereegranskat)abstract
    • Patients with established type 2 diabetes display both beta-cell dysfunction and insulin resistance. To define fundamental processes leading to the diabetic state, we examined the relationship between type 2 diabetes risk variants at 37 established susceptibility loci and indices of proinsulin processing, insulin secretion and insulin sensitivity. We included data from up to 58,614 non-diabetic subjects with basal measures, and 17,327 with dynamic measures. We employed additive genetic models with adjustment for sex, age and BMI, followed by fixed-effects inverse variance meta-analyses. Cluster analyses grouped risk loci into five major categories based on their relationship to these continuous glycemic phenotypes. The first cluster (PPARG, KLF14, IRS1, GCKR) was characterized by primary effects on insulin sensitivity. The second (MTNR1B, GCK) featured risk alleles associated with reduced insulin secretion and fasting hyperglycemia. ARAP1 constituted a third cluster characterized by defects in insulin processing. A fourth cluster (including TCF7L2, SLC30A8, HHEX/IDE, CDKAL1, CDKN2A/2B) was defined by loci influencing insulin processing and secretion without detectable change in fasting glucose. The final group contained twenty risk loci with no clear-cut associations to continuous glycemic traits. By assembling extensive data on continuous glycemic traits, we have exposed the diverse mechanisms whereby type 2 diabetes risk variants impact disease predisposition.
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