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Träfflista för sökning "WFRF:(Lindgren Kristin) srt2:(2020-2022)"

Search: WFRF:(Lindgren Kristin) > (2020-2022)

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1.
  • Yaghootkar, Hanieh, et al. (author)
  • Genetic Studies of Leptin Concentrations Implicate Leptin in the Regulation of Early Adiposity
  • 2020
  • In: Diabetes. - : American Diabetes Association. - 0012-1797 .- 1939-327X. ; 69:12, s. 2806-2818
  • Journal article (peer-reviewed)abstract
    • Leptin influences food intake by informing the brain about the status of body fat stores. Rare LEP mutations associated with congenital leptin deficiency cause severe early-onset obesity that can be mitigated by administering leptin. However, the role of genetic regulation of leptin in polygenic obesity remains poorly understood. We performed an exome-based analysis in up to 57,232 individuals of diverse ancestries to identify genetic variants that influence adiposity-adjusted leptin concentrations. We identify five novel variants, including four missense variants, in LEP, ZNF800, KLHL31, and ACTL9, and one intergenic variant near KLF14. The missense variant Val94Met (rs17151919) in LEP was common in individuals of African ancestry only, and its association with lower leptin concentrations was specific to this ancestry (P = 2 × 10-16, n = 3,901). Using in vitro analyses, we show that the Met94 allele decreases leptin secretion. We also show that the Met94 allele is associated with higher BMI in young African-ancestry children but not in adults, suggesting that leptin regulates early adiposity.
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2.
  • Zhou, Wei, et al. (author)
  • Global Biobank Meta-analysis Initiative : Powering genetic discovery across human disease
  • 2022
  • In: Cell Genomics. - : Elsevier. - 2666-979X. ; 2:10
  • Journal article (peer-reviewed)abstract
    • Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)-a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.
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