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1.
  • Heid, Iris M, et al. (creator_code:aut_t)
  • Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution
  • 2010
  • record:In_t: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 42:11, s. 949-960
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • Waist-hip ratio (WHR) is a measure of body fat distribution and a predictor of metabolic consequences independent of overall adiposity. WHR is heritable, but few genetic variants influencing this trait have been identified. We conducted a meta-analysis of 32 genome-wide association studies for WHR adjusted for body mass index (comprising up to 77,167 participants), following up 16 loci in an additional 29 studies (comprising up to 113,636 subjects). We identified 13 new loci in or near RSPO3, VEGFA, TBX15-WARS2, NFE2L3, GRB14, DNM3-PIGC, ITPR2-SSPN, LY86, HOXC13, ADAMTS9, ZNRF3-KREMEN1, NISCH-STAB1 and CPEB4 (P = 1.9 × 10⁻⁹ to P = 1.8 × 10⁻⁴⁰) and the known signal at LYPLAL1. Seven of these loci exhibited marked sexual dimorphism, all with a stronger effect on WHR in women than men (P for sex difference = 1.9 × 10⁻³ to P = 1.2 × 10⁻¹³). These findings provide evidence for multiple loci that modulate body fat distribution independent of overall adiposity and reveal strong gene-by-sex interactions.
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2.
  • Kanoni, Stavroula, et al. (creator_code:aut_t)
  • Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.
  • 2022
  • record:In_t: Genome biology. - : Springer Science and Business Media LLC. - 1474-760X .- 1465-6906 .- 1474-7596. ; 23:1
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery.To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism.Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.
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3.
  • Ried, Janina S., et al. (creator_code:aut_t)
  • A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape
  • 2016
  • record:In_t: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways.
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4.
  • Lango Allen, Hana, et al. (creator_code:aut_t)
  • Hundreds of variants clustered in genomic loci and biological pathways affect human height.
  • 2010
  • record:In_t: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 467:7317, s. 832-8
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.
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5.
  • Dimas, Antigone S, et al. (creator_code:aut_t)
  • Impact of type 2 diabetes susceptibility variants on quantitative glycemic traits reveals mechanistic heterogeneity.
  • 2014
  • record:In_t: Diabetes. - : American Diabetes Association. - 1939-327X .- 0012-1797. ; 63:6, s. 2158-2171
  • swepub:Mat_article_t (swepub:level_refereed_t)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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6.
  • Benzinou, Michael, et al. (creator_code:aut_t)
  • Common nonsynonymous variants in PCSK1 confer risk of obesity.
  • 2008
  • record:In_t: Nature genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 40:8, s. 943-5
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • Mutations in PCSK1 cause monogenic obesity. To assess the contribution of PCSK1 to polygenic obesity risk, we genotyped tag SNPs in a total of 13,659 individuals of European ancestry from eight independent case-control or family-based cohorts. The nonsynonymous variants rs6232, encoding N221D, and rs6234-rs6235, encoding the Q665E-S690T pair, were consistently associated with obesity in adults and children (P = 7.27 x 10(-8) and P = 2.31 x 10(-12), respectively). Functional analysis showed a significant impairment of the N221D-mutant PC1/3 protein catalytic activity.
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7.
  • Dina, Christian, et al. (creator_code:aut_t)
  • Variation in FTO contributes to childhood obesity and severe adult obesity.
  • 2007
  • record:In_t: Nature genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 39:6, s. 724-6
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • We identified a set of SNPs in the first intron of the FTO (fat mass and obesity associated) gene on chromosome 16q12.2 that is consistently strongly associated with early-onset and severe obesity in both adults and children of European ancestry with an experiment-wise P value of 1.67 x 10(-26) in 2,900 affected individuals and 5,100 controls. The at-risk haplotype yields a proportion of attributable risk of 22% for common obesity. We conclude that FTO contributes to human obesity and hence may be a target for subsequent functional analyses.
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8.
  • Schoch, Conrad L., et al. (creator_code:aut_t)
  • Finding needles in haystacks: linking scientific names, reference specimens and molecular data for Fungi
  • 2014
  • record:In_t: Database: The Journal of Biological Databases and Curation. - : Oxford University Press (OUP). - 1758-0463. ; 2014:bau061, s. 1-21
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • DNA phylogenetic comparisons have shown that morphology-based species recognition often underestimates fungal diversity. Therefore, the need for accurate DNA sequence data, tied to both correct taxonomic names and clearly annotated specimen data, has never been greater. Furthermore, the growing number of molecular ecology and microbiome projects using high-throughput sequencing require fast and effective methods for en masse species assignments. In this article, we focus on selecting and re-annotating a set of marker reference sequences that represent each currently accepted order of Fungi. The particular focus is on sequences from the internal transcribed spacer region in the nuclear ribosomal cistron, derived from type specimens and/or ex-type cultures. Re-annotated and verified sequences were deposited in a curated public database at the National Center for Biotechnology Information (NCBI), namely the RefSeq Targeted Loci (RTL) database, and will be visible during routine sequence similarity searches with NR_prefixed accession numbers. A set of standards and protocols is proposed to improve the data quality of new sequences, and we suggest how type and other reference sequences can be used to improve identification of Fungi.
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9.
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10.
  • Engqvist, Hanna, 1985, et al. (creator_code:aut_t)
  • Integrative genomics approach identifies molecular features associated with early-stage ovarian carcinoma histotypes.
  • 2020
  • record:In_t: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 10:1
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • Ovarian cancer comprises multiple subtypes (clear-cell (CCC), endometrioid (EC), high-grade serous (HGSC), low-grade serous (LGSC), and mucinous carcinomas (MC)) with differing molecular and clinical behavior. However, robust histotype-specific biomarkers for clinical use have yet to be identified. Here, we utilized a multi-omics approach to identify novel histotype-specific genetic markers associated with ovarian carcinoma histotypes (CCC, EC, HGSC, and MC) using DNA methylation, DNA copy number alteration and RNA sequencing data for 96 primary invasive early-stage (stage I and II) ovarian carcinomas. More specifically, the DNA methylation analysis revealed hypermethylation for CCC in comparison with the other histotypes. Moreover, copy number imbalances and novel chromothripsis-like rearrangements (n = 64) were identified in ovarian carcinoma, with the highest number of chromothripsis-like patterns in HGSC. For the 1000 most variable transcripts, underexpression was most prominent for all histotypes in comparison with normal ovarian samples. Overall, the integrative approach identified 46 putative oncogenes (overexpressed, hypomethylated and DNA gain) and three putative tumor suppressor genes (underexpressed, hypermethylated and DNA loss) when comparing the different histotypes. In conclusion, the current study provides novel insights into molecular features associated with early-stage ovarian carcinoma that may improve patient stratification and subclassification of the histotypes.
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