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Item Bivariate genome-wide association meta-analysis of pediatric musculoskeletal traits reveals pleiotropic effects at the SREBF1/TOM1L2 locus(Nature Publishing Group, 2017-07-25) Medina-Gomez, Carolina; Kemp, John P.; Dimou, Niki L.; Kreiner, Eskil; Chesi, Alessandra; Zemel, Babette S.; Bønnelykke, Klaus; Boer, Cindy G.; Ahluwalia, Tarunveer S.; Bisgaard, Hans; Evangelou, Evangelos; Heppe, Denise H.M.; Bonewald, Lynda F.; Gorski, Jeffrey P.; Ghanbari, Mohsen; Demissie, Serkalem; Duque, Gustavo; Maurano, Matthew T.; Kiel, Douglas P.; Hsu, Yi-Hsiang; Eerden, Bram C.J. van der; Ackert-Bicknell, Cheryl; Reppe, Sjur; Gautvik, Kaare M.; Raastad, Truls; Karasik, David; Peppel, Jeroen van de; Jaddoe, Vincent W.V.; Uitterlinden, André G.; Tobias, Jonathan H.; Grant, Struan F.A.; Bagos, Pantelis G.; Evans, David M.; Rivadeneira, Fernando; Anatomy and Cell Biology, School of MedicineBone mineral density is known to be a heritable, polygenic trait whereas genetic variants contributing to lean mass variation remain largely unknown. We estimated the shared SNP heritability and performed a bivariate GWAS meta-analysis of total-body lean mass (TB-LM) and total-body less head bone mineral density (TBLH-BMD) regions in 10,414 children. The estimated SNP heritability is 43% (95% CI: 34-52%) for TBLH-BMD, and 39% (95% CI: 30-48%) for TB-LM, with a shared genetic component of 43% (95% CI: 29-56%). We identify variants with pleiotropic effects in eight loci, including seven established bone mineral density loci: WNT4, GALNT3, MEPE, CPED1/WNT16, TNFSF11, RIN3, and PPP6R3/LRP5. Variants in the TOM1L2/SREBF1 locus exert opposing effects TB-LM and TBLH-BMD, and have a stronger association with the former trait. We show that SREBF1 is expressed in murine and human osteoblasts, as well as in human muscle tissue. This is the first bivariate GWAS meta-analysis to demonstrate genetic factors with pleiotropic effects on bone mineral density and lean mass.Bone mineral density and lean skeletal mass are heritable traits. Here, Medina-Gomez and colleagues perform bivariate GWAS analyses of total body lean mass and bone mass density in children, and show genetic loci with pleiotropic effects on both traits.Item 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 MedicineBackground: 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.Item Genome-wide association study in 79,366 European-ancestry individuals informs the genetic architecture of 25-hydroxyvitamin D levels(Nature Publishing Group, 2018-01-17) Jiang, Xia; O’Reilly, Paul F.; Aschard, Hugues; Hsu, Yi-Hsiang; Richards, J. Brent; Dupuis, Josée; Ingelsson, Erik; Karasik, David; Pilz, Stefan; Berry, Diane; Kestenbaum, Bryan; Zheng, Jusheng; Luan, Jianan; Sofianopoulou, Eleni; Streeten, Elizabeth A.; Albanes, Demetrius; Lutsey, Pamela L.; Yao, Lu; Tang, Weihong; Econs, Michael J.; Wallaschofski, Henri; Völzke, Henry; Zhou, Ang; Power, Chris; McCarthy, Mark I.; Michos, Erin D.; Boerwinkle, Eric; Weinstein, Stephanie J.; Freedman, Neal D.; Huang, Wen-Yi; Van Schoor, Natasja M.; Velde, Nathalie van der; de Groot, Lisette C. P. G. M.; Enneman, Anke; Cupples, L. Adrienne; Booth, Sarah L.; Vasan, Ramachandran S.; Liu, Ching-Ti; Zhou, Yanhua; Ripatti, Samuli; Ohlsson, Claes; Vandenput, Liesbeth; Lorentzon, Mattias; Eriksson, Johan G.; Shea, M. Kyla; Houston, Denise K.; Kritchevsky, Stephen B.; Liu, Yongmei; Lohman, Kurt K.; Ferrucci, Luigi; Peacock, Munro; Gieger, Christian; Beekman, Marian; Slagboom, Eline; Deelen, Joris; Heemst, Diana van; Kleber, Marcus E.; März, Winfried; de Boer, Ian H.; Wood, Alexis C.; Rotter, Jerome I.; Rich, Stephen S.; Robinson-Cohen, Cassianne; Heijer, Martin den; Jarvelin, Marjo-Riitta; Cavadino, Alana; Joshi, Peter K.; Wilson, James F.; Hayward, Caroline; Lind, Lars; Michaëlsson, Karl; Trompet, Stella; Zillikens, M. Carola; Uitterlinden, Andre G.; Rivadeneira, Fernando; Broer, Linda; Zgaga, Lina; Campbell, Harry; Theodoratou, Evropi; Farrington, Susan M.; Timofeeva, Maria; Dunlop, Malcolm G.; Valdes, Ana M.; Tikkanen, Emmi; Lehtimäki, Terho; Lyytikäinen, Leo-Pekka; Kähönen, Mika; Raitakari, Olli T.; Mikkilä, Vera; Ikram, M. Arfan; Sattar, Naveed; Jukema, J. Wouter; Wareham, Nicholas J.; Langenberg, Claudia; Forouhi, Nita G.; Gundersen, Thomas E.; Khaw, Kay-Tee; Butterworth, Adam S.; Danesh, John; Spector, Timothy; Wang, Thomas J.; Hyppönen, Elina; Kraft, Peter; Kiel, Douglas P.; Medicine, School of MedicineVitamin D is a steroid hormone precursor that is associated with a range of human traits and diseases. Previous GWAS of serum 25-hydroxyvitamin D concentrations have identified four genome-wide significant loci (GC, NADSYN1/DHCR7, CYP2R1, CYP24A1). In this study, we expand the previous SUNLIGHT Consortium GWAS discovery sample size from 16,125 to 79,366 (all European descent). This larger GWAS yields two additional loci harboring genome-wide significant variants (P = 4.7×10-9 at rs8018720 in SEC23A, and P = 1.9×10-14 at rs10745742 in AMDHD1). The overall estimate of heritability of 25-hydroxyvitamin D serum concentrations attributable to GWAS common SNPs is 7.5%, with statistically significant loci explaining 38% of this total. Further investigation identifies signal enrichment in immune and hematopoietic tissues, and clustering with autoimmune diseases in cell-type-specific analysis. Larger studies are required to identify additional common SNPs, and to explore the role of rare or structural variants and gene-gene interactions in the heritability of circulating 25-hydroxyvitamin D levelsItem 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 MedicineHip 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.Item Parent-of-origin specific allelic associations among 106 genomic loci for age at menarche(Nature Publishing Group, 2014-10-02) Perry, John RB; Day, Felix; Elks, Cathy E.; Sulem, Patrick; Thompson, Deborah J.; Ferreira, Teresa; He, Chunyan; Chasman, Daniel I.; Esko, Tõnu; Thorleifsson, Gudmar; Albrecht, Eva; Ang, Wei Q.; Corre, Tanguy; Cousminer, Diana L.; Feenstra, Bjarke; Franceschini, Nora; Ganna, Andrea; Johnson, Andrew D.; Kjellqvist, Sanela; Lunetta, Kathryn L.; McMahon, George; Nolte, Ilja M.; Paternoster, Lavinia; Porcu, Eleonora; Smith, Albert V.; Stolk, Lisette; Teumer, Alexander; Tšernikova, Natalia; Tikkanen, Emmi; Ulivi, Sheila; Wagner, Erin K.; Amin, Najaf; Bierut, Laura J.; Byrne, Enda M.; Hottenga, Jouke-Jan; Koller, Daniel L.; Mangino, Massimo; Pers, Tune H.; Yerges-Armstrong, Laura M.; Zhao, Jing Hua; Andrulis, Irene L.; Anton-Culver, Hoda; Atsma, Femke; Bandinelli, Stefania; Beckmann, Matthias W.; Benitez, Javier; Blomqvist, Carl; Bojesen, Stig E.; Bolla, Manjeet K.; Bonanni, Bernardo; Brauch, Hiltrud; Brenner, Hermann; Buring, Julie E.; Chang-Claude, Jenny; Chanock, Stephen; Chen, Jinhui; Chenevix-Trench, Georgia; Collée, J. Margriet; Couch, Fergus J.; Couper, David; Coveillo, Andrea D.; Cox, Angela; Czene, Kamila; D’adamo, Adamo Pio; Smith, George Davey; De Vivo, Immaculata; Demerath, Ellen W.; Dennis, Joe; Devilee, Peter; Dieffenbach, Aida K.; Dunning, Alison M.; Eiriksdottir, Gudny; Eriksson, Johan G.; Fasching, Peter A.; Ferrucci, Luigi; Flesch-Janys, Dieter; Flyger, Henrik; Foroud, Tatiana; Franke, Lude; Garcia, Melissa E.; García-Closas, Montserrat; Geller, Frank; de Geus, Eco EJ; Giles, Graham G.; Gudbjartsson, Daniel F.; Gudnason, Vilmundur; Guénel, Pascal; Guo, Suiqun; Hall, Per; Hamann, Ute; Haring, Robin; Hartman, Catharina A.; Heath, Andrew C.; Hofman, Albert; Hooning, Maartje J.; Hopper, John L.; Hu, Frank B.; Hunter, David J.; Karasik, David; Kiel, Douglas P.; Knight, Julia A.; Kosma, Veli-Matti; Kutalik, Zoltan; Lai, Sandra; Lambrechts, Diether; Lindblom, Annika; Mägi, Reedik; Magnusson, Patrik K.; Mannermaa, Arto; Martin, Nicholas G.; Masson, Gisli; McArdle, Patrick F.; McArdle, Wendy L.; Melbye, Mads; Michailidou, Kyriaki; Mihailov, Evelin; Milani, Lili; Milne, Roger L.; Nevanlinna, Heli; Neven, Patrick; Nohr, Ellen A.; Oldehinkel, Albertine J.; Oostra, Ben A.; Palotie, Aarno; Peacock, Munro; Pedersen, Nancy L.; Peterlongo, Paolo; Peto, Julian; Pharoah, Paul DP; Postma, Dirkje S.; Pouta, Anneli; Pylkäs, Katri; Radice, Paolo; Ring, Susan; Rivadeneira, Fernando; Robino, Antonietta; Rose, Lynda M.; Rudolph, Anja; Salomaa, Veikko; Sanna, Serena; Schlessinger, David; Schmidt, Marjanka K.; Southey, Mellissa C.; Sovio, Ulla; Stampfer, Meir J.; Stöckl, Doris; Storniolo, Anna M.; Timpson, Nicholas J.; Tyrer, Jonathan; Visser, Jenny A.; Vollenweider, Peter; Völzke, Henry; Waeber, Gerard; Waldenberger, Melanie; Wallaschofski, Henri; Wang, Qin; Willemsen, Gonneke; Winqvist, Robert; Wolffenbuttel, Bruce HR; Wright, Margaret J.; Boomsma, Dorret I.; Econs, Michael J.; Khaw, Kay-Tee; Loos, Ruth JF; McCarthy, Mark I.; Montgomery, Grant W.; Rice, John P.; Streeten, Elizabeth A.; Thorsteinsdottir, Unnur; van Duijn, Cornelia M.; Alizadeh, Behrooz Z.; Bergmann, Sven; Boerwinkle, Eric; Boyd, Heather A.; Crisponi, Laura; Gasparini, Paolo; Gieger, Christian; Harris, Tamara B.; Ingelsson, Erik; Järvelin, Marjo-Riitta; Kraft, Peter; Lawlor, Debbie; Metspalu, Andres; Pennell, Craig E.; Ridker, Paul M.; Snieder, Harold; Sørensen, Thorkild IA; Spector, Tim D.; Strachan, David P.; Uitterlinden, André G.; Wareham, Nicholas J.; Widen, Elisabeth; Zygmunt, Marek; Murray, Anna; Easton, Douglas F.; Stefansson, Kari; Murabito, Joanne M.; Ong, Ken K.; Department of Epidemiology, Richard M. Fairbanks School of Public HealthAge at menarche is a marker of timing of puberty in females. It varies widely between individuals, is a heritable trait and is associated with risks for obesity, type 2 diabetes, cardiovascular disease, breast cancer and all-cause mortality. Studies of rare human disorders of puberty and animal models point to a complex hypothalamic-pituitary-hormonal regulation,, but the mechanisms that determine pubertal timing and underlie its links to disease risk remain unclear. Here, using genome-wide and custom-genotyping arrays in up to 182,416 women of European descent from 57 studies, we found robust evidence (P<5×10−8) for 123 signals at 106 genomic loci associated with age at menarche. Many loci were associated with other pubertal traits in both sexes, and there was substantial overlap with genes implicated in body mass index and various diseases, including rare disorders of puberty. Menarche signals were enriched in imprinted regions, with three loci (DLK1/WDR25, MKRN3/MAGEL2 and KCNK9) demonstrating parent-of-origin specific associations concordant with known parental expression patterns. Pathway analyses implicated nuclear hormone receptors, particularly retinoic acid and gamma-aminobutyric acid-B2 receptor signaling, among novel mechanisms that regulate pubertal timing in humans. Our findings suggest a genetic architecture involving at least hundreds of common variants in the coordinated timing of the pubertal transition.Item Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program(Springer Nature, 2021) Taliun, Daniel; Harris, Daniel N.; Kessler, Michael D.; Carlson, Jedidiah; Szpiech, Zachary A.; Torres, Raul; Gagliano Taliun, Sarah A.; Corvelo, André; Gogarten, Stephanie M.; Kang, Hyun Min; Pitsillides, Achilleas N.; LeFaive, Jonathon; Lee, Seung-Been; Tian, Xiaowen; Browning, Brian L.; Das, Sayantan; Emde, Anne-Katrin; Clarke, Wayne E.; Loesch, Douglas P.; Shetty, Amol C.; Blackwell, Thomas W.; Smith, Albert V.; Wong, Quenna; Liu, Xiaoming; Conomos, Matthew P.; Bobo, Dean M.; Aguet, François; Albert, Christine; Alonso, Alvaro; Ardlie, Kristin G.; Arking, Dan E.; Aslibekyan, Stella; Auer, Paul L.; Barnard, John; Barr, R. Graham; Barwick, Lucas; Becker, Lewis C.; Beer, Rebecca L.; Benjamin, Emelia J.; Bielak, Lawrence F.; Blangero, John; Boehnke, Michael; Bowden, Donald W.; Brody, Jennifer A.; Burchard, Esteban G.; Cade, Brian E.; Casella, James F.; Chalazan, Brandon; Chasman, Daniel I.; Chen, Yii-Der Ida; Cho, Michael H.; Choi, Seung Hoan; Chung, Mina K.; Clish, Clary B.; Correa, Adolfo; Curran, Joanne E.; Custer, Brian; Darbar, Dawood; Daya, Michelle; de Andrade, Mariza; DeMeo, Dawn L.; Dutcher, Susan K.; Ellinor, Patrick T.; Emery, Leslie S.; Eng, Celeste; Fatkin, Diane; Fingerlin, Tasha; Forer, Lukas; Fornage, Myriam; Franceschini, Nora; Fuchsberger, Christian; Fullerton, Stephanie M.; Germer, Soren; Gladwin, Mark T.; Gottlieb, Daniel J.; Guo, Xiuqing; Hall, Michael E.; He, Jiang; Heard-Costa, Nancy L.; Heckbert, Susan R.; Irvin, Marguerite R.; Johnsen, Jill M.; Johnson, Andrew D.; Kaplan, Robert; Kardia, Sharon L. R.; Kelly, Tanika; Kelly, Shannon; Kenny, Eimear E.; Kiel, Douglas P.; Klemmer, Robert; Konkle, Barbara A.; Kooperberg, Charles; Köttgen, Anna; Lange, Leslie A.; Lasky-Su, Jessica; Levy, Daniel; Lin, Xihong; Lin, Keng-Han; Liu, Chunyu; Loos, Ruth J. F.; Garman, Lori; Gerszten, Robert; Lubitz, Steven A.; Lunetta, Kathryn L.; Mak, Angel C. Y.; Manichaikul, Ani; Manning, Alisa K.; Mathias, Rasika A.; McManus, David D.; McGarvey, Stephen T.; Meigs, James B.; Meyers, Deborah A.; Mikulla, Julie L.; Minear, Mollie A.; Mitchell, Braxton D.; Mohanty, Sanghamitra; Montasser, May E.; Montgomery, Courtney; Morrison, Alanna C.; Murabito, Joanne M.; Natale, Andrea; Natarajan, Pradeep; Nelson, Sarah C.; North, Kari E.; O'Connell, Jeffrey R.; Palmer, Nicholette D.; Pankratz, Nathan; Peloso, Gina M.; Peyser, Patricia A.; Pleiness, Jacob; Post, Wendy S.; Psaty, Bruce M.; Rao, D. C.; Redline, Susan; Reiner, Alexander P.; Roden, Dan; Rotter, Jerome I.; Ruczinski, Ingo; Sarnowski, Chloé; Schoenherr, Sebastian; Schwartz, David A.; Seo, Jeong-Sun; Seshadri, Sudha; Sheehan, Vivien A.; Sheu, Wayne H.; Shoemaker, M. Benjamin; Smith, Nicholas L.; Smith, Jennifer A.; Sotoodehnia, Nona; Stilp, Adrienne M.; Tang, Weihong; Taylor, Kent D.; Telen, Marilyn; Thornton, Timothy A.; Tracy, Russell P.; Van Den Berg, David J.; Vasan, Ramachandran S.; Viaud-Martinez, Karine A.; Vrieze, Scott; Weeks, Daniel E.; Weir, Bruce S.; Weiss, Scott T.; Weng, Lu-Chen; Willer, Cristen J.; Zhang, Yingze; Zhao, Xutong; Arnett, Donna K.; Ashley-Koch, Allison E.; Barnes, Kathleen C.; Boerwinkle, Eric; Gabriel, Stacey; Gibbs, Richard; Rice, Kenneth M.; Rich, Stephen S.; Silverman, Edwin K.; Qasba, Pankaj; Gan, Weiniu; NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium; Papanicolaou, George J.; Nickerson, Deborah A.; Browning, Sharon R.; Zody, Michael C.; Zöllner, Sebastian; Wilson, James G.; Cupples, L. Adrienne; Laurie, Cathy C.; Jaquish, Cashell E.; Hernandez, Ryan D.; O'Connor, Timothy D.; Abecasis, Gonçalo R.; Epidemiology, Richard M. Fairbanks School of Public HealthThe Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.Item The Musculoskeletal Knowledge Portal: improving access to multi-omics data(Springer Nature, 2022) Westendorf, Jennifer J.; Bonewald, Lynda F.; Kiel, Douglas P.; Burtt, Noël P.; Anatomy, Cell Biology and Physiology, School of Medicine