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Träfflista för sökning "WFRF:(Stefansson H) ;hsvcat:1"

Search: WFRF:(Stefansson H) > Natural sciences

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1.
  • Ramdas, S., et al. (author)
  • A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids
  • 2022
  • In: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 109:8, s. 1366-1387
  • Journal article (peer-reviewed)abstract
    • A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.
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2.
  • Mishra, A., et al. (author)
  • Stroke genetics informs drug discovery and risk prediction across ancestries
  • 2022
  • In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 611
  • Journal article (peer-reviewed)abstract
    • Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.
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4.
  • Saevarsdottir, S., et al. (author)
  • Multiomics analysis of rheumatoid arthritis yields sequence variants that have large effects on risk of the seropositive subset
  • 2022
  • In: Annals of the Rheumatic Diseases. - : BMJ. - 0003-4967 .- 1468-2060. ; 81:8
  • Journal article (peer-reviewed)abstract
    • Objectives To find causal genes for rheumatoid arthritis (RA) and its seropositive (RF and/or ACPA positive) and seronegative subsets. Methods We performed a genome-wide association study (GWAS) of 31 313 RA cases (68% seropositive) and similar to 1 million controls from Northwestern Europe. We searched for causal genes outside the HLA-locus through effect on coding, mRNA expression in several tissues and/or levels of plasma proteins (SomaScan) and did network analysis (Qiagen). Results We found 25 sequence variants for RA overall, 33 for seropositive and 2 for seronegative RA, altogether 37 sequence variants at 34 non-HLA loci, of which 15 are novel. Genomic, transcriptomic and proteomic analysis of these yielded 25 causal genes in seropositive RA and additional two overall. Most encode proteins in the network of interferon-alpha/beta and IL-12/23 that signal through the JAK/STAT-pathway. Highlighting those with largest effect on seropositive RA, a rare missense variant in STAT4 (rs140675301-A) that is independent of reported non-coding STAT4-variants, increases the risk of seropositive RA 2.27-fold (p=2.1x10(-9)), more than the rs2476601-A missense variant in PTPN22 (OR=1.59, p=1.3x10(-160)). STAT4 rs140675301-A replaces hydrophilic glutamic acid with hydrophobic valine (Glu128Val) in a conserved, surface-exposed loop. A stop-mutation (rs76428106-C) in FLT3 increases seropositive RA risk (OR=1.35, p=6.6x10(-11)). Independent missense variants in TYK2 (rs34536443-C, rs12720356-C, rs35018800-A, latter two novel) associate with decreased risk of seropositive RA (ORs=0.63-0.87, p=10(-9)-10(-27)) and decreased plasma levels of interferon-alpha/beta receptor 1 that signals through TYK2/JAK1/STAT4. Conclusion Sequence variants pointing to causal genes in the JAK/STAT pathway have largest effect on seropositive RA, while associations with seronegative RA remain scarce.
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5.
  • Turcot, Valerie, et al. (author)
  • Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity
  • 2018
  • In: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 50:1, s. 26-41
  • Journal article (peer-reviewed)abstract
    • Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are similar to 10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed similar to 7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.
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6.
  • Berndt, Sonja I., et al. (author)
  • Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture
  • 2013
  • In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:5, s. 501-U69
  • Journal article (peer-reviewed)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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8.
  • Marouli, Eirini, et al. (author)
  • Rare and low-frequency coding variants alter human adult height
  • 2017
  • In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 542:7640, s. 186-190
  • Journal article (peer-reviewed)abstract
    • Height is a highly heritable, classic polygenic trait with approximately 700 common associated variants identified through genome-wide association studies so far. Here, we report 83 height-associated coding variants with lower minor-allele frequencies (in the range of 0.1-4.8%) and effects of up to 2 centimetres per allele (such as those in IHH, STC2, AR and CRISPLD2), greater than ten times the average effect of common variants. In functional follow-up studies, rare height increasing alleles of STC2 (giving an increase of 1-2 centimetres per allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes that are mutated in monogenic growth disorders and highlight new biological candidates (such as ADAMTS3, IL11RA and NOX4) and pathways (such as proteoglycan and glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate-to-large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways.
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9.
  • Thorgeirsson, T. E., et al. (author)
  • A rare missense mutation in CHRNA4 associates with smoking behavior and its consequences
  • 2016
  • In: Molecular Psychiatry. - : Springer Science and Business Media LLC. - 1359-4184 .- 1476-5578. ; 21:5, s. 594-600
  • Journal article (peer-reviewed)abstract
    • Using Icelandic whole-genome sequence data and an imputation approach we searched for rare sequence variants in CHRNA4 and tested them for association with nicotine dependence. We show that carriers of a rare missense variant (allele frequency = 0.24%) within CHRNA4, encoding an R336C substitution, have greater risk of nicotine addiction than non-carriers as assessed by the Fagerstrom Test for Nicotine Dependence (P = 1.2 x 10(-4)). The variant also confers risk of several serious smoking-related diseases previously shown to be associated with the D398N substitution in CHRNA5. We observed odds ratios (ORs) of 1.7-2.3 for lung cancer (LC; P = 4.0 x 10(-4)), chronic obstructive pulmonary disease (COPD; P = 9.3 x 10(-4)), peripheral artery disease (PAD; P = 0.090) and abdominal aortic aneurysms (AAAs; P = 0.12), and the variant associates strongly with the early-onset forms of LC (OR = 4.49, P = 2.2 x 10(-4)), COPD (OR = 3.22, P = 2.9 x 10(-4)), PAD (OR = 3.47, P = 9.2 x 10(-3)) and AAA (OR = 6.44, P = 6.3 x 10(-3)). Joint analysis of the four smoking-related diseases reveals significant association (P = 6.8 x 10(-5)), particularly for early-onset cases (P = 2.1 x 10(-7)). Our results are in agreement with functional studies showing that the human alpha 4 beta 2 isoform of the channel containing R336C has less sensitivity for its agonists than the wild-type form following nicotine incubation.
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10.
  • Smith, Jennifer A, et al. (author)
  • Genome-wide association study identifies 74 loci associated with educational attainment
  • 2016
  • In: Nature (London). - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 533:7604, s. 539-542
  • Journal article (peer-reviewed)abstract
    • Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.
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