Browsing by Author "Akesson, Kristina"

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    Disentangling the genetics of lean mass
    (Oxford University Press, 2019-02-01) Karasik, David; Zillikens, M. Carola; Hsu, Yi-Hsiang; Aghdassi, Ali; Akesson, Kristina; Amin, Najaf; Barroso, Inês; Bennett, David A.; Bertram, Lars; Bochud, Murielle; Borecki, Ingrid B.; Broer, Linda; Buchman, Aron S.; Byberg, Liisa; Campbell, Harry; Campos-Obando, Natalia; Cauley, Jane A.; Cawthon, Peggy M.; Chambers, John C.; Chen, Zhao; Cho, Nam H.; Choi, Hyung Jin; Chou, Wen-Chi; Cummings, Steven R.; De Groot, Lisette C. P. G. M.; De Jager, Phillip L.; Demuth, Ilja; Diatchenko, Luda; Econs, Michael J.; Eiriksdottir, Gudny; Enneman, Anke W.; Eriksson, Joel; Eriksson, Johan G.; Estrada, Karol; Evans, Daniel S.; Feitosa, Mary F.; Fu, Mao; Gieger, Christian; Grallert, Harald; Gudnason, Vilmundur; Lenore, Launer J.; Hayward, Caroline; Hofman, Albert; Homuth, Georg; Huffman, Kim M.; Husted, Lise B.; Illig, Thomas; Ingelsson, Erik; Ittermann, Till; Jansson, John-Olov; Johnson, Toby; Biffar, Reiner; Jordan, Joanne M.; Jula, Antti; Karlsson, Magnus; Khaw, Kay-Tee; Kilpeläinen, Tuomas O.; Klopp, Norman; Kloth, Jacqueline S. L.; Koller, Daniel L.; Kooner, Jaspal S.; Kraus, William E.; Kritchevsky, Stephen; Kutalik, Zoltán; Kuulasmaa, Teemu; Kuusisto, Johanna; Laakso, Markku; Lahti, Jari; Lang, Thomas; Langdahl, Bente L.; Lerch, Markus M.; Lewis, Joshua R.; Lill, Christina; Lind, Lars; Lindgren, Cecilia; Liu, Yongmei; Livshits, Gregory; Ljunggren, Östen; Loos, Ruth J. F.; Lorentzon, Mattias; Luan, Jian'an; Luben, Robert N.; Malkin, Ida; McGuigan, Fiona E.; Medina-Gomez, Carolina; Meitinger, Thomas; Melhus, Håkan; Mellström, Dan; Michaëlsson, Karl; Mitchell, Braxton D.; Morris, Andrew P.; Mosekilde, Leif; Nethander, Maria; Newman, Anne B.; O'Connell, Jeffery R.; Oostra, Ben A.; Orwoll, Eric S.; Palotie, Aarno; Peacock, Munro; Perola, Markus; Peters, Annette; Prince, Richard L.; Psaty, Bruce M.; Räikkönen, Katri; Ralston, Stuart H.; Ripatti, Samuli; Rivadeneira, Fernando; Robbins, John A.; Rotter, Jerome I.; Rudan, Igor; Salomaa, Veikko; Satterfield, Suzanne; Schipf, Sabine; Shin, Chan Soo; Smith, Albert V.; Smith, Shad B.; Soranzo, Nicole; Spector, Timothy D.; Stančáková, Alena; Stefansson, Kari; Steinhagen-Thiessen, Elisabeth; Stolk, Lisette; Streeten, Elizabeth A.; Styrkarsdottir, Unnur; Swart, Karin M. A.; Thompson, Patricia; Thomson, Cynthia A.; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Tikkanen, Emmi; Tranah, Gregory J.; Uitterlinden, André G.; Van Duijn, Cornelia M.; Van Schoor, Natasja M.; Vandenput, Liesbeth; Vollenweider, Peter; Völzke, Henry; Wactawski-Wende, Jean; Walker, Mark; Wareham, Nicholas J.; Waterworth, Dawn; Weedon, Michael N.; Wichmann, H-Erich.; Widen, Elisabeth; Williams, Frances M. K.; Wilson, James F.; Wright, Nicole C.; Yerges-Armstrong, Laura M.; Yu, Lei; Zhang, Weihua; Zhao, Jing Hua; Zhou, Yanhua; Nielson, Carrie M.; Harris, Tamara B.; Demissie, Serkalem; Kiel, Douglas P.; Ohlsson, Claes; Medicine, School of Medicine
    Background: Lean body mass (LM) plays an important role in mobility and metabolic function. We previously identified five loci associated with LM adjusted for fat mass in kilograms. Such an adjustment may reduce the power to identify genetic signals having an association with both lean mass and fat mass. Objectives: To determine the impact of different fat mass adjustments on genetic architecture of LM and identify additional LM loci. Methods: We performed genome-wide association analyses for whole-body LM (20 cohorts of European ancestry with n = 38,292) measured using dual-energy X-ray absorptiometry) or bioelectrical impedance analysis, adjusted for sex, age, age2, and height with or without fat mass adjustments (Model 1 no fat adjustment; Model 2 adjustment for fat mass as a percentage of body mass; Model 3 adjustment for fat mass in kilograms). Results: Seven single-nucleotide polymorphisms (SNPs) in separate loci, including one novel LM locus (TNRC6B), were successfully replicated in an additional 47,227 individuals from 29 cohorts. Based on the strengths of the associations in Model 1 vs Model 3, we divided the LM loci into those with an effect on both lean mass and fat mass in the same direction and refer to those as "sumo wrestler" loci (FTO and MC4R). In contrast, loci with an impact specifically on LM were termed "body builder" loci (VCAN and ADAMTSL3). Using existing available genome-wide association study databases, LM increasing alleles of SNPs in sumo wrestler loci were associated with an adverse metabolic profile, whereas LM increasing alleles of SNPs in "body builder" loci were associated with metabolic protection. Conclusions: In conclusion, we identified one novel LM locus (TNRC6B). Our results suggest that a genetically determined increase in lean mass might exert either harmful or protective effects on metabolic traits, depending on its relation to fat mass.
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    Meta-analysis of genome-wide studies identifies WNT16 and ESR1 SNPs associated with bone mineral density in premenopausal women
    (Oxford University Press, 2013) Koller, Daniel L.; Zheng, Hou-Feng; Karasik, David; Yerges-Armstrong, Laura; Liu, Ching-Ti; McGuigan, Fiona; Kemp, John P.; Giroux, Sylvie; Lai, Dongbing; Edenberg, Howard J.; Peacock, Munro; Czerwinski, Stefan A.; Choh, Audrey C.; McMahon, George; St. Pourcain, Beate; Timpson, Nicholas J.; Lawlor, Debbie A.; Evans, David M.; Towne, Bradford; Blangero, John; Carless, Melanie A.; Kammerer, Candace; Goltzman, David; Kovacs, Christopher S.; Prior, Jerilynn C.; Spector, Tim D.; Rousseau, Francois; Tobias, Jon H.; Akesson, Kristina; Econs, Michael J.; Mitchell, Braxton D.; Richards, J. Brent; Kiel, Douglas P.; Foroud, Tatiana; Medical and Molecular Genetics, School of Medicine
    Previous genome-wide association studies (GWAS) have identified common variants in genes associated with variation in bone mineral density (BMD), although most have been carried out in combined samples of older women and men. Meta-analyses of these results have identified numerous single-nucleotide polymorphisms (SNPs) of modest effect at genome-wide significance levels in genes involved in both bone formation and resorption, as well as other pathways. We performed a meta-analysis restricted to premenopausal white women from four cohorts (n = 4061 women, aged 20 to 45 years) to identify genes influencing peak bone mass at the lumbar spine and femoral neck. After imputation, age- and weight-adjusted bone-mineral density (BMD) values were tested for association with each SNP. Association of an SNP in the WNT16 gene (rs3801387; p = 1.7 × 10(-9) ) and multiple SNPs in the ESR1/C6orf97 region (rs4870044; p = 1.3 × 10(-8) ) achieved genome-wide significance levels for lumbar spine BMD. These SNPs, along with others demonstrating suggestive evidence of association, were then tested for association in seven replication cohorts that included premenopausal women of European, Hispanic-American, and African-American descent (combined n = 5597 for femoral neck; n = 4744 for lumbar spine). When the data from the discovery and replication cohorts were analyzed jointly, the evidence was more significant (WNT16 joint p = 1.3 × 10(-11) ; ESR1/C6orf97 joint p = 1.4 × 10(-10) ). Multiple independent association signals were observed with spine BMD at the ESR1 region after conditioning on the primary signal. Analyses of femoral neck BMD also supported association with SNPs in WNT16 and ESR1/C6orf97 (p < 1 × 10(-5) ). Our results confirm that several of the genes contributing to BMD variation across a broad age range in both sexes have effects of similar magnitude on BMD of the spine in premenopausal women. These data support the hypothesis that variants in these genes of known skeletal function also affect BMD during the premenopausal period.
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    Meta-Analysis of Genomewide Association Studies Reveals Genetic Variants for Hip Bone Geometry
    (Wiley, 2019-07) Hsu, Yi-Hsiang; Estrada, Karol; Evangelou, Evangelos; Ackert-Bicknell, Cheryl; Akesson, Kristina; Beck, Thomas; Brown, Suzanne J.; Capellini, Terence; Carbone, Laura; Cauley, Jane; Cheung, Ching-Lung; Cummings, Steven R.; Czerwinski, Stefan; Demissie, Serkalem; Econs, Michael; Evans, Daniel; Farber, Charles; Gautvik, Kaare; Harris, Tamara; Kammerer, Candace; Kemp, John; Koller, Daniel L.; Kung, Annie; Lawlor, Debbie; Lee, Miryoung; Lorentzon, Mattias; McGuigan, Fiona; Medina-Gomez, Carolina; Mitchell, Braxton; Newman, Anne; Nielson, Carrie; Ohlsson, Claes; Peacock, Munro; Reppe, Sjur; Richards, J. Brent; Robbins, John; Sigurdsson, Gunnar; Spector, Timothy D.; Stefansson, Kari; Streeten, Elizabeth; Styrkarsdottir, Unnur; Tobias, Jonathan; Trajanoska, Katerina; Uitterlinden, André; Vandenput, Liesbeth; Wilson, Scott G.; Yerges-Armstrong, Laura; Young, Mariel; Zillikens, Carola; Rivadeneira, Fernando; Kiel, Douglas P.; Karasik, David; Medicine, School of Medicine
    Hip geometry is an important predictor of fracture. We performed a meta-analysis of GWAS studies in adults to identify genetic variants that are associated with proximal femur geometry phenotypes. We analyzed four phenotypes: (i) femoral neck length; (ii) neck-shaft angle; (iii) femoral neck width, and (iv) femoral neck section modulus, estimated from DXA scans using algorithms of hip structure analysis. In the Discovery stage, 10 cohort studies were included in the fixed-effect meta-analysis, with up to 18,719 men and women ages 16 to 93 years. Association analyses were performed with ∼2.5 million polymorphisms under an additive model adjusted for age, body mass index, and height. Replication analyses of meta-GWAS significant loci (at adjusted genomewide significance [GWS], threshold p ≤ 2.6 × 10-8 ) were performed in seven additional cohorts in silico. We looked up SNPs associated in our analysis, for association with height, bone mineral density (BMD), and fracture. In meta-analysis (combined Discovery and Replication stages), GWS associations were found at 5p15 (IRX1 and ADAMTS16); 5q35 near FGFR4; at 12p11 (in CCDC91); 11q13 (near LRP5 and PPP6R3 (rs7102273)). Several hip geometry signals overlapped with BMD, including LRP5 (chr. 11). Chr. 11 SNP rs7102273 was associated with any-type fracture (p = 7.5 × 10-5 ). We used bone transcriptome data and discovered several significant eQTLs, including rs7102273 and PPP6R3 expression (p = 0.0007), and rs6556301 (intergenic, chr.5 near FGFR4) and PDLIM7 expression (p = 0.005). In conclusion, we found associations between several genes and hip geometry measures that explained 12% to 22% of heritability at different sites. The results provide a defined set of genes related to biological pathways relevant to BMD and etiology of bone fragility.