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Träfflista för sökning "WFRF:(Lahti Jari) ;lar1:(gu);pers:(Mahajan Anubha)"

Search: WFRF:(Lahti Jari) > University of Gothenburg > Mahajan Anubha

  • Result 1-5 of 5
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1.
  • Kilpeläinen, Tuomas O, et al. (author)
  • Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels
  • 2016
  • In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7
  • Journal article (peer-reviewed)abstract
    • Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching P<10(-6) in 19,979 additional individuals. We identify five loci robustly associated (P<5 × 10(-8)) with leptin levels in/near LEP, SLC32A1, GCKR, CCNL1 and FTO. Although the association of the FTO obesity locus with leptin levels is abolished by adjustment for BMI, associations of the four other loci are independent of adiposity. The GCKR locus was found associated with multiple metabolic traits in previous GWAS and the CCNL1 locus with birth weight. Knockdown experiments in mouse adipose tissue explants show convincing evidence for adipogenin, a regulator of adipocyte differentiation, as the novel causal gene in the SLC32A1 locus influencing leptin levels. Our findings provide novel insights into the regulation of leptin production by adipose tissue and open new avenues for examining the influence of variation in leptin levels on adiposity and metabolic health.
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2.
  • Lind, Lars, et al. (author)
  • Genome Wide Association Identifies Common Variants at the SERPINA6/SERPINA1 Locus Influencing Plasma Cortisol and Corticosteroid Binding Globulin.
  • 2014
  • In: PLoS genetics. - : Public Library of Science (PLoS). - 1553-7404 .- 1553-7390. ; 10:7
  • Journal article (peer-reviewed)abstract
    • Variation in plasma levels of cortisol, an essential hormone in the stress response, is associated in population-based studies with cardio-metabolic, inflammatory and neuro-cognitive traits and diseases. Heritability of plasma cortisol is estimated at 30-60% but no common genetic contribution has been identified. The CORtisol NETwork (CORNET) consortium undertook genome wide association meta-analysis for plasma cortisol in 12,597 Caucasian participants, replicated in 2,795 participants. The results indicate that <1% of variance in plasma cortisol is accounted for by genetic variation in a single region of chromosome 14. This locus spans SERPINA6, encoding corticosteroid binding globulin (CBG, the major cortisol-binding protein in plasma), and SERPINA1, encoding α1-antitrypsin (which inhibits cleavage of the reactive centre loop that releases cortisol from CBG). Three partially independent signals were identified within the region, represented by common SNPs; detailed biochemical investigation in a nested sub-cohort showed all these SNPs were associated with variation in total cortisol binding activity in plasma, but some variants influenced total CBG concentrations while the top hit (rs12589136) influenced the immunoreactivity of the reactive centre loop of CBG. Exome chip and 1000 Genomes imputation analysis of this locus in the CROATIA-Korcula cohort identified missense mutations in SERPINA6 and SERPINA1 that did not account for the effects of common variants. These findings reveal a novel common genetic source of variation in binding of cortisol by CBG, and reinforce the key role of CBG in determining plasma cortisol levels. In turn this genetic variation may contribute to cortisol-associated degenerative diseases.
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3.
  • Lu, Yingchang, et al. (author)
  • New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk
  • 2016
  • In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7
  • Journal article (peer-reviewed)abstract
    • To increase our understanding of the genetic basis of adiposity and its links to cardiometabolic disease risk, we conducted a genome-wide association meta-analysis of body fat percentage (BF%) in up to 100,716 individuals. Twelve loci reached genome-wide significance (P<5 × 10(-8)), of which eight were previously associated with increased overall adiposity (BMI, BF%) and four (in or near COBLL1/GRB14, IGF2BP1, PLA2G6, CRTC1) were novel associations with BF%. Seven loci showed a larger effect on BF% than on BMI, suggestive of a primary association with adiposity, while five loci showed larger effects on BMI than on BF%, suggesting association with both fat and lean mass. In particular, the loci more strongly associated with BF% showed distinct cross-phenotype association signatures with a range of cardiometabolic traits revealing new insights in the link between adiposity and disease risk.
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4.
  • Middeldorp, Christel M., et al. (author)
  • The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia : design, results and future prospects
  • 2019
  • In: European Journal of Epidemiology. - : Springer Science and Business Media LLC. - 0393-2990 .- 1573-7284. ; 34:3, s. 279-300
  • Journal article (peer-reviewed)abstract
    • The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.
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5.
  • Ried, Janina S., et al. (author)
  • A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape
  • 2016
  • In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7
  • Journal article (peer-reviewed)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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journal article (5)
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peer-reviewed (5)
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Eriksson, Johan G. (5)
Uitterlinden, André ... (5)
Raitakari, Olli T (4)
Ohlsson, Claes, 1965 (4)
Grarup, Niels (4)
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Hofman, Albert (4)
Paternoster, Lavinia (4)
Palotie, Aarno (4)
Vandenput, Liesbeth, ... (3)
Jula, Antti (3)
Perola, Markus (3)
Lind, Lars (3)
Campbell, Harry (3)
Rudan, Igor (3)
Wareham, Nicholas J. (3)
McCarthy, Mark I (3)
Linneberg, Allan (3)
Eriksson, Joel (3)
Jørgensen, Torben (3)
Langenberg, Claudia (3)
Mohlke, Karen L (3)
Scott, Robert A (3)
Ingelsson, Erik (3)
Hunter, David J (3)
Havulinna, Aki S. (3)
Kähönen, Mika (3)
Lehtimäki, Terho (3)
Verweij, Niek (3)
Koskinen, Seppo (3)
Mangino, Massimo (3)
Gieger, Christian (3)
Peters, Annette (3)
Heliövaara, Markku (3)
Vohl, Marie-Claude (3)
Luan, Jian'an (3)
Männistö, Satu (3)
Sørensen, Thorkild I ... (3)
Jousilahti, Pekka (3)
Evans, David M (3)
Loos, Ruth J F (3)
Hayward, Caroline (3)
Hirschhorn, Joel N. (3)
van der Harst, Pim (3)
Timpson, Nicholas J. (3)
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University
Lund University (4)
Uppsala University (3)
Karolinska Institutet (3)
Umeå University (2)
Örebro University (1)
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Language
English (5)
Research subject (UKÄ/SCB)
Medical and Health Sciences (5)
Natural sciences (2)

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