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Sökning: WFRF:(Bhangale T)

  • Resultat 1-9 av 9
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1.
  • Tabassum, R, et al. (författare)
  • Genetic architecture of human plasma lipidome and its link to cardiovascular disease
  • 2019
  • Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 4329-
  • Tidskriftsartikel (refereegranskat)abstract
    • Understanding genetic architecture of plasma lipidome could provide better insights into lipid metabolism and its link to cardiovascular diseases (CVDs). Here, we perform genome-wide association analyses of 141 lipid species (n = 2,181 individuals), followed by phenome-wide scans with 25 CVD related phenotypes (n = 511,700 individuals). We identify 35 lipid-species-associated loci (P <5 ×10−8), 10 of which associate with CVD risk including five new loci-COL5A1, GLTPD2, SPTLC3, MBOAT7 and GALNT16 (false discovery rate<0.05). We identify loci for lipid species that are shown to predict CVD e.g., SPTLC3 for CER(d18:1/24:1). We show that lipoprotein lipase (LPL) may more efficiently hydrolyze medium length triacylglycerides (TAGs) than others. Polyunsaturated lipids have highest heritability and genetic correlations, suggesting considerable genetic regulation at fatty acids levels. We find low genetic correlations between traditional lipids and lipid species. Our results show that lipidomic profiles capture information beyond traditional lipids and identify genetic variants modifying lipid levels and risk of CVD.
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  • Bronson, P. G., et al. (författare)
  • Common variants at PVT1, ATG13-AMBRA1, AHI1 and CLEC16A are associated with selective IgA deficiency
  • 2016
  • Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 48:11, s. 1425-1429
  • Tidskriftsartikel (refereegranskat)abstract
    • Selective immunoglobulin A deficiency (IgAD) is the most common p rimary immunodeficiency in Europeans. Our genome-wide association study (GWAS) meta-analysis of 1,635 patients with IgAD and 4,852 controls identified four new significant (P < 5 x 10(-8)) loci and association with a rare IFIH1 variant (p.11e923Val). Peak new variants (PVT1, P = 4.3 x 10(-11); ATG13-AMBRA1, P = 6.7 x 10(-10); AHI1, P = 8.4 x 10(-10); CLEC16A, P = 1.4 x 10(-9)) overlapped with autoimmune markers (3/4) and correlated with 21 putative regulatory variants, including expression quantitative trait loci (eQTLs) for AHI1 and DEXI and DNase hypersensitivity sites in FOXP3(+) regulatory T cells. Pathway analysis of the meta-analysis results showed striking association with the KEGG pathway for IgA production (pathway P < 0.0001), with 22 of the 30 annotated pathway genes containing at least one variant with P <= 0.05 in the IgAD meta-analysis. These data suggest that a complex network of genetic effects, including genes known to influence the biology of IgA production, contributes to IgAD.
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  • Asselbergs, Folkert W., et al. (författare)
  • Large-Scale Gene-Centric Meta-analysis across 32 Studies Identifies Multiple Lipid Loci
  • 2012
  • Ingår i: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297. ; 91:5, s. 823-838
  • Tidskriftsartikel (refereegranskat)abstract
    • Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom similar to 50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering similar to 2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids.
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  • Langefeld, Carl D., et al. (författare)
  • Transancestral mapping and genetic load in systemic lupus erythematosus
  • 2017
  • Ingår i: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 8
  • Tidskriftsartikel (refereegranskat)abstract
    • Systemic lupus erythematosus (SLE) is an autoimmune disease with marked gender and ethnic disparities. We report a large transancestral association study of SLE using Immunochip genotype data from 27,574 individuals of European (EA), African (AA) and Hispanic Amerindian (HA) ancestry. We identify 58 distinct non-HLA regions in EA, 9 in AA and 16 in HA (similar to 50% of these regions have multiple independent associations); these include 24 novel SLE regions (P < 5 x 10(-8)), refined association signals in established regions, extended associations to additional ancestries, and a disentangled complex HLA multigenic effect. The risk allele count (genetic load) exhibits an accelerating pattern of SLE risk, leading us to posit a cumulative hit hypothesis for autoimmune disease. Comparing results across the three ancestries identifies both ancestry-dependent and ancestry-independent contributions to SLE risk. Our results are consistent with the unique and complex histories of the populations sampled, and collectively help clarify the genetic architecture and ethnic disparities in SLE.
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  • Lango Allen, Hana, et al. (författare)
  • Hundreds of variants clustered in genomic loci and biological pathways affect human height.
  • 2010
  • Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 467:7317, s. 832-8
  • Tidskriftsartikel (refereegranskat)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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