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3. Factors Contributing to Uptake of Stillbirth Evaluations: A Qualitative Analysis.

Author

Riches, Naomi O., Workalemahu, Tsegaselassie, Johnson, Erin P., Lopez, Sarah, Blue, Nathan, Page, Jessica, Silver, Robert M., and Rothwell, Erin

Subjects
*HEALTH care teams, *STILLBIRTH, *GENETIC testing, *DECISION making, *AUTOPSY
Abstract

ABSTRACT Objective Design Setting Population Methods Main Outcome Measures Results Conclusion Funding The purpose of this study was to explore individuals' beliefs, values, and experiences surrounding stillbirth evaluation decisions.Qualitative research.University of Utah Health.Parents who experienced a stillbirth in the past 5 years (n = 19) were interviewed about their experiences and decision to consent to or decline stillbirth evaluations, such as autopsy, placental histopathology, or genetic testing.Qualitative content analysis.Barriers and facilitators to parentsstillbirth postmortem decision‐making.Participants communicated several facilitators and barriers that contributed to their stillbirth evaluation decision. Reasons for consenting to evaluations were belief in science, background in medicine, altruism, to inform future pregnancies, thinking about preventing another stillbirth, and how patients viewed the care of their stillborn by the medical team. Reasons for declining evaluations were receiving a diagnosis prior to being offered a postmortem evaluation, intent to avoid causing further harm to the baby, interest to spend more time with their baby, and cost of the evaluation.Stillbirth is one of the most difficult experiences of a parent. Diagnostic and emotional barriers create further challenges to decision‐making for stillbirth postmortem evaluations. Parents often rely on inadequate information and personal values and beliefs during this time‐sensitive decision process. Decision support for stillbirth evaluations and training for medical providers could benefit parents, may increase stillbirth evaluation uptake, and potentially prevent decisional regret.Research reported in this publication was supported by the Utah Centre for Excellence in ELSI Research (UCEER). [ABSTRACT FROM AUTHOR]

Published
2024
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6. Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults.

Author

Graff, Mariaelisa, Scott, Robert A, Justice, Anne E, Young, Kristin L, Feitosa, Mary F, Barata, Llilda, Winkler, Thomas W, Chu, Audrey Y, Mahajan, Anubha, Hadley, David, Xue, Luting, Workalemahu, Tsegaselassie, Heard-Costa, Nancy L, den Hoed, Marcel, Ahluwalia, Tarunveer S, Qi, Qibin, Ngwa, Julius S, Renström, Frida, Quaye, Lydia, Eicher, John D, Hayes, James E, Cornelis, Marilyn, Kutalik, Zoltan, Lim, Elise, Luan, Jian'an, Huffman, Jennifer E, Zhang, Weihua, Zhao, Wei, Griffin, Paula J, Haller, Toomas, Ahmad, Shafqat, Marques-Vidal, Pedro M, Bien, Stephanie, Yengo, Loic, Teumer, Alexander, Smith, Albert Vernon, Kumari, Meena, Harder, Marie Neergaard, Justesen, Johanne Marie, Kleber, Marcus E, Hollensted, Mette, Lohman, Kurt, Rivera, Natalia V, Whitfield, John B, Zhao, Jing Hua, Stringham, Heather M, Lyytikäinen, Leo-Pekka, Huppertz, Charlotte, Willemsen, Gonneke, Peyrot, Wouter J, Wu, Ying, Kristiansson, Kati, Demirkan, Ayse, Fornage, Myriam, Hassinen, Maija, Bielak, Lawrence F, Cadby, Gemma, Tanaka, Toshiko, Mägi, Reedik, van der Most, Peter J, Jackson, Anne U, Bragg-Gresham, Jennifer L, Vitart, Veronique, Marten, Jonathan, Navarro, Pau, Bellis, Claire, Pasko, Dorota, Johansson, Åsa, Snitker, Søren, Cheng, Yu-Ching, Eriksson, Joel, Lim, Unhee, Aadahl, Mette, Adair, Linda S, Amin, Najaf, Balkau, Beverley, Auvinen, Juha, Beilby, John, Bergman, Richard N, Bergmann, Sven, Bertoni, Alain G, Blangero, John, Bonnefond, Amélie, Bonnycastle, Lori L, Borja, Judith B, Brage, Søren, Busonero, Fabio, Buyske, Steve, Campbell, Harry, Chines, Peter S, Collins, Francis S, Corre, Tanguy, Smith, George Davey, Delgado, Graciela E, Dueker, Nicole, Dörr, Marcus, Ebeling, Tapani, Eiriksdottir, Gudny, Esko, Tõnu, and Faul, Jessica D

Subjects
CHARGE Consortium, EPIC-InterAct Consortium, PAGE Consortium, Humans, Obesity, Genetic Predisposition to Disease, Body Mass Index, Waist-Hip Ratio, Exercise, Genotype, Female, Male, Adiposity, Waist Circumference, Genome-Wide Association Study, Epigenomics, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Genetics, Developmental Biology
Abstract

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.

Published
2017

11. New genetic loci link adipose and insulin biology to body fat distribution

Author

Shungin, Dmitry, Winkler, Thomas W, Croteau-Chonka, Damien C, Ferreira, Teresa, Locke, Adam E, Mägi, Reedik, Strawbridge, Rona J, Pers, Tune H, Fischer, Krista, Justice, Anne E, Workalemahu, Tsegaselassie, Wu, Joseph MW, Buchkovich, Martin L, Heard-Costa, Nancy L, Roman, Tamara S, Drong, Alexander W, Song, Ci, Gustafsson, Stefan, Day, Felix R, Esko, Tonu, Fall, Tove, Kutalik, Zoltán, Luan, Jian’an, Randall, Joshua C, Scherag, André, Vedantam, Sailaja, Wood, Andrew R, Chen, Jin, Fehrmann, Rudolf, Karjalainen, Juha, Kahali, Bratati, Liu, Ching-Ti, Schmidt, Ellen M, Absher, Devin, Amin, Najaf, Anderson, Denise, Beekman, Marian, Bragg-Gresham, Jennifer L, Buyske, Steven, Demirkan, Ayse, Ehret, Georg B, Feitosa, Mary F, Goel, Anuj, Jackson, Anne U, Johnson, Toby, Kleber, Marcus E, Kristiansson, Kati, Mangino, Massimo, Mateo Leach, Irene, Medina-Gomez, Carolina, Palmer, Cameron D, Pasko, Dorota, Pechlivanis, Sonali, Peters, Marjolein J, Prokopenko, Inga, Stančáková, Alena, Ju Sung, Yun, Tanaka, Toshiko, Teumer, Alexander, Van Vliet-Ostaptchouk, Jana V, Yengo, Loïc, Zhang, Weihua, Albrecht, Eva, Ärnlöv, Johan, Arscott, Gillian M, Bandinelli, Stefania, Barrett, Amy, Bellis, Claire, Bennett, Amanda J, Berne, Christian, Blüher, Matthias, Böhringer, Stefan, Bonnet, Fabrice, Böttcher, Yvonne, Bruinenberg, Marcel, Carba, Delia B, Caspersen, Ida H, Clarke, Robert, Warwick Daw, E, Deelen, Joris, Deelman, Ewa, Delgado, Graciela, Doney, Alex SF, Eklund, Niina, Erdos, Michael R, Estrada, Karol, Eury, Elodie, Friedrich, Nele, Garcia, Melissa E, Giedraitis, Vilmantas, Gigante, Bruna, Go, Alan S, Golay, Alain, Grallert, Harald, Grammer, Tanja B, Gräßler, Jürgen, Grewal, Jagvir, Groves, Christopher J, Haller, Toomas, and Hallmans, Goran

Subjects
Genetics, Human Genome, Diabetes, Obesity, Nutrition, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Cardiovascular, Stroke, Adipocytes, Adipogenesis, Adipose Tissue, Age Factors, Body Fat Distribution, Body Mass Index, Epigenesis, Genetic, Europe, Female, Genome, Human, Genome-Wide Association Study, Humans, Insulin, Insulin Resistance, Male, Models, Biological, Neovascularization, Physiologic, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Racial Groups, Sex Characteristics, Transcription, Genetic, Waist-Hip Ratio, ADIPOGen Consortium, CARDIOGRAMplusC4D Consortium, CKDGen Consortium, GEFOS Consortium, GENIE Consortium, GLGC, ICBP, International Endogene Consortium, LifeLines Cohort Study, MAGIC Investigators, MuTHER Consortium, PAGE Consortium, ReproGen Consortium, General Science & Technology
Abstract

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P

Published
2015

12. Genetic studies of body mass index yield new insights for obesity biology

Author

Locke, Adam E, Kahali, Bratati, Berndt, Sonja I, Justice, Anne E, Pers, Tune H, Day, Felix R, Powell, Corey, Vedantam, Sailaja, Buchkovich, Martin L, Yang, Jian, Croteau-Chonka, Damien C, Esko, Tonu, Fall, Tove, Ferreira, Teresa, Gustafsson, Stefan, Kutalik, Zoltán, Luan, Jian’an, Mägi, Reedik, Randall, Joshua C, Winkler, Thomas W, Wood, Andrew R, Workalemahu, Tsegaselassie, Faul, Jessica D, Smith, Jennifer A, Hua Zhao, Jing, Zhao, Wei, Chen, Jin, Fehrmann, Rudolf, Hedman, Åsa K, Karjalainen, Juha, Schmidt, Ellen M, Absher, Devin, Amin, Najaf, Anderson, Denise, Beekman, Marian, Bolton, Jennifer L, Bragg-Gresham, Jennifer L, Buyske, Steven, Demirkan, Ayse, Deng, Guohong, Ehret, Georg B, Feenstra, Bjarke, Feitosa, Mary F, Fischer, Krista, Goel, Anuj, Gong, Jian, Jackson, Anne U, Kanoni, Stavroula, Kleber, Marcus E, Kristiansson, Kati, Lim, Unhee, Lotay, Vaneet, Mangino, Massimo, Mateo Leach, Irene, Medina-Gomez, Carolina, Medland, Sarah E, Nalls, Michael A, Palmer, Cameron D, Pasko, Dorota, Pechlivanis, Sonali, Peters, Marjolein J, Prokopenko, Inga, Shungin, Dmitry, Stančáková, Alena, Strawbridge, Rona J, Ju Sung, Yun, Tanaka, Toshiko, Teumer, Alexander, Trompet, Stella, van der Laan, Sander W, van Setten, Jessica, Van Vliet-Ostaptchouk, Jana V, Wang, Zhaoming, Yengo, Loïc, Zhang, Weihua, Isaacs, Aaron, Albrecht, Eva, Ärnlöv, Johan, Arscott, Gillian M, Attwood, Antony P, Bandinelli, Stefania, Barrett, Amy, Bas, Isabelita N, Bellis, Claire, Bennett, Amanda J, Berne, Christian, Blagieva, Roza, Blüher, Matthias, Böhringer, Stefan, Bonnycastle, Lori L, Böttcher, Yvonne, Boyd, Heather A, Bruinenberg, Marcel, Caspersen, Ida H, Ida Chen, Yii-Der, Clarke, Robert, Warwick Daw, E, de Craen, Anton JM, Delgado, Graciela, and Dimitriou, Maria

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Obesity, Pediatric, Nutrition, Biotechnology, Human Genome, Childhood Obesity, Prevention, 2.1 Biological and endogenous factors, 1.1 Normal biological development and functioning, Metabolic and endocrine, Stroke, Oral and gastrointestinal, Adipogenesis, Adiposity, Age Factors, Body Mass Index, Energy Metabolism, Europe, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Glutamic Acid, Humans, Insulin, Insulin Secretion, Male, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Racial Groups, Synapses, LifeLines Cohort Study, ADIPOGen Consortium, AGEN-BMI Working Group, CARDIOGRAMplusC4D Consortium, CKDGen Consortium, GLGC, ICBP, MAGIC Investigators, MuTHER Consortium, MIGen Consortium, PAGE Consortium, ReproGen Consortium, GENIE Consortium, International Endogene Consortium, General Science & Technology
Abstract

Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P 20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

Published
2015

13. Defining the role of common variation in the genomic and biological architecture of adult human height

Author

Wood, Andrew R, Esko, Tonu, Yang, Jian, Vedantam, Sailaja, Pers, Tune H, Gustafsson, Stefan, Chu, Audrey Y, Estrada, Karol, Luan, Jian'an, Kutalik, Zoltán, Amin, Najaf, Buchkovich, Martin L, Croteau-Chonka, Damien C, Day, Felix R, Duan, Yanan, Fall, Tove, Fehrmann, Rudolf, Ferreira, Teresa, Jackson, Anne U, Karjalainen, Juha, Lo, Ken Sin, Locke, Adam E, Mägi, Reedik, Mihailov, Evelin, Porcu, Eleonora, Randall, Joshua C, Scherag, André, Vinkhuyzen, Anna AE, Westra, Harm-Jan, Winkler, Thomas W, Workalemahu, Tsegaselassie, Zhao, Jing Hua, Absher, Devin, Albrecht, Eva, Anderson, Denise, Baron, Jeffrey, Beekman, Marian, Demirkan, Ayse, Ehret, Georg B, Feenstra, Bjarke, Feitosa, Mary F, Fischer, Krista, Fraser, Ross M, Goel, Anuj, Gong, Jian, Justice, Anne E, Kanoni, Stavroula, Kleber, Marcus E, Kristiansson, Kati, Lim, Unhee, Lotay, Vaneet, Lui, Julian C, Mangino, Massimo, Leach, Irene Mateo, Medina-Gomez, Carolina, Nalls, Michael A, Nyholt, Dale R, Palmer, Cameron D, Pasko, Dorota, Pechlivanis, Sonali, Prokopenko, Inga, Ried, Janina S, Ripke, Stephan, Shungin, Dmitry, Stancáková, Alena, Strawbridge, Rona J, Sung, Yun Ju, Tanaka, Toshiko, Teumer, Alexander, Trompet, Stella, van der Laan, Sander W, van Setten, Jessica, Van Vliet-Ostaptchouk, Jana V, Wang, Zhaoming, Yengo, Loïc, Zhang, Weihua, Afzal, Uzma, Ärnlöv, Johan, Arscott, Gillian M, Bandinelli, Stefania, Barrett, Amy, Bellis, Claire, Bennett, Amanda J, Berne, Christian, Blüher, Matthias, Bolton, Jennifer L, Böttcher, Yvonne, Boyd, Heather A, Bruinenberg, Marcel, Buckley, Brendan M, Buyske, Steven, Caspersen, Ida H, Chines, Peter S, Clarke, Robert, Claudi-Boehm, Simone, Cooper, Matthew, Daw, E Warwick, De Jong, Pim A, Deelen, Joris, and Delgado, Graciela

Subjects
Biological Sciences, Genetics, Human Genome, 2.1 Biological and endogenous factors, Adult, Analysis of Variance, Body Height, Genetic Variation, Genetics, Population, Genome-Wide Association Study, Humans, Oligonucleotide Array Sequence Analysis, Polymorphism, Single Nucleotide, White People, Electronic Medical Records and Genomics (eMEMERGEGE) Consortium, MIGen Consortium, PAGEGE Consortium, LifeLines Cohort Study, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.

Published
2014

15. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index

Author

Speliotes, Elizabeth K, Willer, Cristen J, Berndt, Sonja I, Monda, Keri L, Thorleifsson, Gudmar, Jackson, Anne U, Allen, Hana Lango, Lindgren, Cecilia M, Luan, Jian'an, Mägi, Reedik, Randall, Joshua C, Vedantam, Sailaja, Winkler, Thomas W, Qi, Lu, Workalemahu, Tsegaselassie, Heid, Iris M, Steinthorsdottir, Valgerdur, Stringham, Heather M, Weedon, Michael N, Wheeler, Eleanor, Wood, Andrew R, Ferreira, Teresa, Weyant, Robert J, Segrè, Ayellet V, Estrada, Karol, Liang, Liming, Nemesh, James, Park, Ju-Hyun, Gustafsson, Stefan, Kilpeläinen, Tuomas O, Yang, Jian, Bouatia-Naji, Nabila, Esko, Tõnu, Feitosa, Mary F, Kutalik, Zoltán, Mangino, Massimo, Raychaudhuri, Soumya, Scherag, Andre, Smith, Albert Vernon, Welch, Ryan, Zhao, Jing Hua, Aben, Katja K, Absher, Devin M, Amin, Najaf, Dixon, Anna L, Fisher, Eva, Glazer, Nicole L, Goddard, Michael E, Heard-Costa, Nancy L, Hoesel, Volker, Hottenga, Jouke-Jan, Johansson, Åsa, Johnson, Toby, Ketkar, Shamika, Lamina, Claudia, Li, Shengxu, Moffatt, Miriam F, Myers, Richard H, Narisu, Narisu, Perry, John RB, Peters, Marjolein J, Preuss, Michael, Ripatti, Samuli, Rivadeneira, Fernando, Sandholt, Camilla, Scott, Laura J, Timpson, Nicholas J, Tyrer, Jonathan P, van Wingerden, Sophie, Watanabe, Richard M, White, Charles C, Wiklund, Fredrik, Barlassina, Christina, Chasman, Daniel I, Cooper, Matthew N, Jansson, John-Olov, Lawrence, Robert W, Pellikka, Niina, Prokopenko, Inga, Shi, Jianxin, Thiering, Elisabeth, Alavere, Helene, Alibrandi, Maria TS, Almgren, Peter, Arnold, Alice M, Aspelund, Thor, Atwood, Larry D, Balkau, Beverley, Balmforth, Anthony J, Bennett, Amanda J, Ben-Shlomo, Yoav, Bergman, Richard N, Bergmann, Sven, Biebermann, Heike, Blakemore, Alexandra IF, Boes, Tanja, Bonnycastle, Lori L, Bornstein, Stefan R, Brown, Morris J, and Buchanan, Thomas A

Subjects
Biological Sciences, Genetics, Human Genome, Obesity, Nutrition, 2.1 Biological and endogenous factors, Body Height, Body Mass Index, Body Size, Body Weight, Chromosome Mapping, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, White People, MAGIC, Procardis Consortium, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼ 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10⁻⁸), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.

Published
2010

16. Hundreds of variants clustered in genomic loci and biological pathways affect human height

Author

Lango Allen, Hana, Estrada, Karol, Lettre, Guillaume, Berndt, Sonja I, Weedon, Michael N, Rivadeneira, Fernando, Willer, Cristen J, Jackson, Anne U, Vedantam, Sailaja, Raychaudhuri, Soumya, Ferreira, Teresa, Wood, Andrew R, Weyant, Robert J, Segrè, Ayellet V, Speliotes, Elizabeth K, Wheeler, Eleanor, Soranzo, Nicole, Park, Ju-Hyun, Yang, Jian, Gudbjartsson, Daniel, Heard-Costa, Nancy L, Randall, Joshua C, Qi, Lu, Vernon Smith, Albert, Mägi, Reedik, Pastinen, Tomi, Liang, Liming, Heid, Iris M, Luan, Jian’an, Thorleifsson, Gudmar, Winkler, Thomas W, Goddard, Michael E, Sin Lo, Ken, Palmer, Cameron, Workalemahu, Tsegaselassie, Aulchenko, Yurii S, Johansson, Åsa, Carola Zillikens, M, Feitosa, Mary F, Esko, Tõnu, Johnson, Toby, Ketkar, Shamika, Kraft, Peter, Mangino, Massimo, Prokopenko, Inga, Absher, Devin, Albrecht, Eva, Ernst, Florian, Glazer, Nicole L, Hayward, Caroline, Hottenga, Jouke-Jan, Jacobs, Kevin B, Knowles, Joshua W, Kutalik, Zoltán, Monda, Keri L, Polasek, Ozren, Preuss, Michael, Rayner, Nigel W, Robertson, Neil R, Steinthorsdottir, Valgerdur, Tyrer, Jonathan P, Voight, Benjamin F, Wiklund, Fredrik, Xu, Jianfeng, Hua Zhao, Jing, Nyholt, Dale R, Pellikka, Niina, Perola, Markus, Perry, John RB, Surakka, Ida, Tammesoo, Mari-Liis, Altmaier, Elizabeth L, Amin, Najaf, Aspelund, Thor, Bhangale, Tushar, Boucher, Gabrielle, Chasman, Daniel I, Chen, Constance, Coin, Lachlan, Cooper, Matthew N, Dixon, Anna L, Gibson, Quince, Grundberg, Elin, Hao, Ke, Juhani Junttila, M, Kaplan, Lee M, Kettunen, Johannes, König, Inke R, Kwan, Tony, Lawrence, Robert W, Levinson, Douglas F, Lorentzon, Mattias, McKnight, Barbara, Morris, Andrew P, Müller, Martina, Suh Ngwa, Julius, Purcell, Shaun, Rafelt, Suzanne, Salem, Rany M, and Salvi, Erika

Subjects
Biological Sciences, Genetics, Health Sciences, Mathematical Sciences, Statistics, Human Genome, Biotechnology, 2.1 Biological and endogenous factors, Body Height, Chromosomes, Human, Pair 3, Genetic Loci, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Metabolic Networks and Pathways, Multifactorial Inheritance, Phenotype, Polymorphism, Single Nucleotide, General Science & Technology
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

Published
2010

21. Associations of cardiometabolic polygenic risk scores with cardiovascular disease in African Americans

Author

Workalemahu, Tsegaselassie, primary, Ying, Jian, additional, G., Berhanu Gebremeskel, additional, Lu, Tianyuan, additional, Mohanty, April, additional, Elfassy, Tali, additional, Tekola-Ayele, Fasil, additional, A., Timothy Thornton, additional, Cohen, Jordana, additional, R., Marguerite Irvin, additional, M., Robert Silver, additional, W., Michael Varner, additional, Yaffe, Kristine, additional, Fornage, Myriam, additional, M., Donald Lloyd-Jones, additional, Sims, Mario, additional, Shimbo, Daichi, additional, Yano, Yuichiro, additional, Muntner, Paul, additional, and Bress, Adam, additional

Published
2023
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23. Familial Risk of Placental Abruption

Author

Dalton, Susan, primary, Meeks, Huong, additional, Fraser, Alison, additional, Etcitty, Devin, additional, Workalemahu, Tsegaselassie, additional, Varner, Michael, additional, and (USA), Robert Silver, additional

Published
2023
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24. Copy number variants and fetal structural abnormalities in stillborn fetuses: A secondary analysis of the Stillbirth Collaborative Research Network study

Author

Workalemahu, Tsegaselassie, primary, Dalton, Susan, additional, Son, Shannon L., additional, Allshouse, Amanda, additional, Carey, Andrew Z., additional, Page, Jessica M., additional, Blue, Nathan R., additional, Thorsten, Vanessa, additional, Goldenberg, Robert L., additional, Pinar, Halit, additional, Reddy, Uma M., additional, and Silver, Robert M., additional

Published
2023
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27. Copy number variants and fetal structural abnormalities in stillborn fetuses: A secondary analysis of the Stillbirth Collaborative Research Network study.

Author

Workalemahu, Tsegaselassie, Dalton, Susan, Son, Shannon L., Allshouse, Amanda, Carey, Andrew Z., Page, Jessica M., Blue, Nathan R., Thorsten, Vanessa, Goldenberg, Robert L., Pinar, Halit, Reddy, Uma M., and Silver, Robert M.

Subjects
*DNA copy number variations, *FETAL abnormalities, *STILLBIRTH, *SECONDARY analysis, *HYDROPS fetalis, *SINGLE nucleotide polymorphisms
Abstract

Objective: To examine the association of placental and fetal DNA copy number variants (CNVs) with fetal structural malformations (FSMs) in stillborn fetuses. Design: A secondary analysis of stillbirth cases in the Stillbirth Collaborative Research Network (SCRN) study. Setting: Multicenter, 59 hospitals in five geographic regions in the USA. Population: 388 stillbirth cases of the SCRN study (2006–2008). Methods: Fetal structural malformations were grouped by anatomic system and specific malformation type (e.g. central nervous system, thoracic, cardiac, gastrointestinal, skeletal, umbilical cord and craniofacial defects). Single‐nucleotide polymorphism array detected CNVs of at least 500 kb. CNVs were classified into two groups: normal, defined as no CNVs >500 kb or benign CNVs, and abnormal, defined as pathogenic or variants of unknown clinical significance. Main outcome measures: The proportions of abnormal CNVs and normal CNVs were compared between stillbirth cases with and without FSMs using the Wald Chi‐square test. Results: The proportion of stillbirth cases with any FSMs was higher among those with abnormal CNVs than among those with normal CNVs (47.5 versus 19.1%; P‐value <0.001). The most common organ system‐specific FSMs associated with abnormal CNVs were cardiac defects, followed by hydrops, craniofacial defects and skeletal defects. A pathogenic deletion of 1q21.1 involving 46 genes (e.g. CHD1L) and a duplication of 21q22.13 involving four genes (SIM2, CLDN14, CHAF1B, HLCS) were associated with a skeletal and cardiac defect, respectively. Conclusion: Specific CNVs involving several genes were associated with FSMs in stillborn fetuses. The findings warrant further investigation and may inform counselling and care surrounding pregnancies affected by FSMs at risk for stillbirth. [ABSTRACT FROM AUTHOR]

Published
2024
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31. Associations of maternal blood pressure-raising polygenic risk scores with fetal weight

Author

Workalemahu, Tsegaselassie, Rahman, Mohammad L., Ouidir, Marion, Wu, Jing, Zhang, Cuilin, and Tekola-Ayele, Fasil

Abstract

Maternal blood pressure (BP) is associated with variations in fetal weight, an important determinant of neonatal and adult health. However, the association of BP-raising genetic risk with fetal weight is unknown. We tested the associations of maternal BP-raising polygenic risk scores (PRS) with estimated fetal weights (EFWs) at 13, 20, 27, and 40 weeks of gestation. This study included 622 White, 637 Black, 568 Hispanic, and 238 Asian pregnant women with genotype data from the NICHD Fetal Growth Studies. PRS of systolic (SBP) and diastolic BP (DBP) were calculated for each participant based on summary statistics from a recent genome-wide association study. Linear regression models were used to compare mean EFW differences between the highest versus lowest tertile of PRS, adjusting for maternal age, education, parity, genetic principal components and fetal sex. Hispanics in the highest DBP PRS tertile, compared to those in the lowest, had 8.1 g (95% CI: −15.1, −1.1), 32.4 g (−58.4, −6.4) and 119.4 g (−218.1, −20.7) lower EFW at 20, 27 and 40 weeks, respectively. Similarly, Asians in the highest DBP PRS tertile had 137.2 g (−263.5, −10.8) lower EFW at week 40, and those in the highest tertile of SBP PRS had 3.2 g (−5.8, −0.7), 12.9 g (−23.5, −2.4), and 39.8 g (−76.9, −2.7) lower EFWs at 13, 20, and 27 weeks. The findings showed that pregnant women’s genetic susceptibility to high BP contributes to reduced fetal growth, suggesting a potential future clinical application in perinatal health.

Published
2024
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32. Copy number variants and fetal structural abnormalities in stillborn fetuses: a secondary analysis of the Stillbirth Collaborative Research Network study

Author

Workalemahu, Tsegaselassie, primary, Dalton, Susan, additional, Son, Shannon, additional, Allshouse, Amanda, additional, Carey, Andrew, additional, Page, Jessica, additional, Blue, Nathan, additional, Thorsten, Vanessa, additional, Goldenberg, Robert, additional, Pinar, Halit, additional, Reddy, Uma, additional, and (USA), Robert Silver, additional

Published
2022
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33. Familial aggregation of stillbirth: A pedigree analysis of a matched case–control study

Author

Workalemahu, Tsegaselassie, primary, Page, Jessica M., additional, Meeks, Huong, additional, Yu, Zhe, additional, Guinto, Emily, additional, Fraser, Alison, additional, Varner, Michael W., additional, Theilen, Lauren H., additional, Quinlan, Aaron, additional, Coon, Hilary, additional, Enquobahrie, Daniel A., additional, Ananth, Cande V., additional, Tekola‐Ayele, Fasil, additional, Jorde, Lynn B., additional, and Silver, Robert M., additional

Published
2022
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34. Meta-analysis of Gene-Level Associations for Rare Variants Based on Single-Variant Statistics

Author

Berndt, Sonja I., Gustafsson, Stefan, Mägi, Reedik, Ganna, Andrea, Wheeler, Eleanor, Feitosa, Mary F., Justice, Anne E., Monda, Keri L., Croteau-Chonka, Damien C., Day, Felix R., Esko, Tõnu, Fall, Tove, Ferreira, Teresa, Gentilini, Davide, Jackson, Anne U., Luan, Jian’an, Randall, Joshua C., Vedantam, Sailaja, Willer, Cristen J., Winkler, Thomas W., Wood, Andrew R., Workalemahu, Tsegaselassie, Hu, Yi-Juan, Lee, Sang Hong, Liang, Liming, Lin, Dan-Yu, Min, Josine L., Neale, Benjamin M., Thorleifsson, Gudmar, Yang, Jian, Albrecht, Eva, Amin, Najaf, Bragg-Gresham, Jennifer L., Cadby, Gemma, den Heijer, Martin, Eklund, Niina, Fischer, Krista, Goel, Anuj, Hottenga, Jouke-Jan, Huffman, Jennifer E., Jarick, Ivonne, Johansson, Åsa, Johnson, Toby, Kanoni, Stavroula, Kleber, Marcus E., König, Inke R., Kristiansson, Kati, Kutalik, Zoltán, Lamina, Claudia, Lecoeur, Cecile, Li, Guo, Mangino, Massimo, McArdle, Wendy L., Medina-Gomez, Carolina, Müller-Nurasyid, Martina, Ngwa, Julius S., Nolte, Ilja M., Paternoster, Lavinia, Pechlivanis, Sonali, Perola, Markus, Peters, Marjolein J., Preuss, Michael, Rose, Lynda M., Shi, Jianxin, Shungin, Dmitry, Smith, Albert Vernon, Strawbridge, Rona J., Surakka, Ida, Teumer, Alexander, Trip, Mieke D., Tyrer, Jonathan, Van Vliet-Ostaptchouk, Jana V., Vandenput, Liesbeth, Waite, Lindsay L., Zhao, Jing Hua, Absher, Devin, Asselbergs, Folkert W., Atalay, Mustafa, Attwood, Antony P., Balmforth, Anthony J., Basart, Hanneke, Beilby, John, Bonnycastle, Lori L., Brambilla, Paolo, Bruinenberg, Marcel, Campbell, Harry, Chasman, Daniel I., Chines, Peter S., Collins, Francis S., Connell, John M., Cookson, William, de Faire, Ulf, de Vegt, Femmie, Dei, Mariano, Dimitriou, Maria, Edkins, Sarah, Estrada, Karol, Evans, David M., Farrall, Martin, Ferrario, Marco M., Ferrières, Jean, Franke, Lude, Frau, Francesca, Gejman, Pablo V., Grallert, Harald, Grönberg, Henrik, Gudnason, Vilmundur, Hall, Alistair S., Hall, Per, Hartikainen, Anna-Liisa, Hayward, Caroline, Heard-Costa, Nancy L., Heath, Andrew C., Hebebrand, Johannes, Homuth, Georg, Hu, Frank B., Hunt, Sarah E., Hyppönen, Elina, Iribarren, Carlos, Jacobs, Kevin B., Jansson, John-Olov, Jula, Antti, Kähönen, Mika, Kathiresan, Sekar, Kee, Frank, Khaw, Kay-Tee, Kivimaki, Mika, Koenig, Wolfgang, Kraja, Aldi T., Kumari, Meena, Kuulasmaa, Kari, Kuusisto, Johanna, Laitinen, Jaana H., Lakka, Timo A., Langenberg, Claudia, Launer, Lenore J., Lind, Lars, Lindström, Jaana, Liu, Jianjun, Liuzzi, Antonio, Lokki, Marja-Liisa, Lorentzon, Mattias, Madden, Pamela A., Magnusson, Patrik K., Manunta, Paolo, Marek, Diana, März, Winfried, Leach, Irene Mateo, McKnight, Barbara, Medland, Sarah E., Mihailov, Evelin, Milani, Lili, Montgomery, Grant W., Mooser, Vincent, Mühleisen, Thomas W., Munroe, Patricia B., Musk, Arthur W., Narisu, Narisu, Navis, Gerjan, Nicholson, George, Nohr, Ellen A., Ong, Ken K., Oostra, Ben A., Palmer, Colin N.A., Palotie, Aarno, Peden, John F., Pedersen, Nancy, Peters, Annette, Polasek, Ozren, Pouta, Anneli, Pramstaller, Peter P., Prokopenko, Inga, Pütter, Carolin, Radhakrishnan, Aparna, Raitakari, Olli, Rendon, Augusto, Rivadeneira, Fernando, Rudan, Igor, Saaristo, Timo E., Sambrook, Jennifer G., Sanders, Alan R., Sanna, Serena, Saramies, Jouko, Schipf, Sabine, Schreiber, Stefan, Schunkert, Heribert, Shin, So-Youn, Signorini, Stefano, Sinisalo, Juha, Skrobek, Boris, Soranzo, Nicole, Stančáková, Alena, Stark, Klaus, Stephens, Jonathan C., Stirrups, Kathleen, Stolk, Ronald P., Stumvoll, Michael, Swift, Amy J., Theodoraki, Eirini V., Thorand, Barbara, Tregouet, David-Alexandre, Tremoli, Elena, Van der Klauw, Melanie M., van Meurs, Joyce B.J., Vermeulen, Sita H., Viikari, Jorma, Virtamo, Jarmo, Vitart, Veronique, Waeber, Gérard, Wang, Zhaoming, Widén, Elisabeth, Wild, Sarah H., Willemsen, Gonneke, Winkelmann, Bernhard R., Witteman, Jacqueline C.M., Wolffenbuttel, Bruce H.R., Wong, Andrew, Wright, Alan F., Zillikens, M. Carola, Amouyel, Philippe, Boehm, Bernhard O., Boerwinkle, Eric, Boomsma, Dorret I., Caulfield, Mark J., Chanock, Stephen J., Cupples, L. Adrienne, Cusi, Daniele, Dedoussis, George V., Erdmann, Jeanette, Eriksson, Johan G., Franks, Paul W., Froguel, Philippe, Gieger, Christian, Gyllensten, Ulf, Hamsten, Anders, Harris, Tamara B., Hengstenberg, Christian, Hicks, Andrew A., Hingorani, Aroon, Hinney, Anke, Hofman, Albert, Hovingh, Kees G., Hveem, Kristian, Illig, Thomas, Jarvelin, Marjo-Riitta, Jöckel, Karl-Heinz, Keinanen-Kiukaanniemi, Sirkka M., Kiemeney, Lambertus A., Kuh, Diana, Laakso, Markku, Lehtimäki, Terho, Levinson, Douglas F., Martin, Nicholas G., Metspalu, Andres, Morris, Andrew D., Nieminen, Markku S., Njølstad, Inger, Ohlsson, Claes, Oldehinkel, Albertine J., Ouwehand, Willem H., Palmer, Lyle J., Penninx, Brenda, Power, Chris, Province, Michael A., Psaty, Bruce M., Qi, Lu, Rauramaa, Rainer, Ridker, Paul M., Ripatti, Samuli, Salomaa, Veikko, Samani, Nilesh J., Snieder, Harold, Sørensen, Thorkild I.A., Spector, Timothy D., Stefansson, Kari, Tönjes, Anke, Tuomilehto, Jaakko, Uitterlinden, André G., Uusitupa, Matti, van der Harst, Pim, Vollenweider, Peter, Wallaschofski, Henri, Wareham, Nicholas J., Watkins, Hugh, Wichmann, H.-Erich, Wilson, James F., Abecasis, Goncalo R., Assimes, Themistocles L., Barroso, Inês, Boehnke, Michael, Borecki, Ingrid B., Deloukas, Panos, Fox, Caroline S., Frayling, Timothy, Groop, Leif C., Haritunian, Talin, Heid, Iris M., Hunter, David, Kaplan, Robert C., Karpe, Fredrik, Moffatt, Miriam, Mohlke, Karen L., O’Connell, Jeffrey R., Pawitan, Yudi, Schadt, Eric E., Schlessinger, David, Steinthorsdottir, Valgerdur, Strachan, David P., Thorsteinsdottir, Unnur, van Duijn, Cornelia M., Visscher, Peter M., Di Blasio, Anna Maria, Hirschhorn, Joel N., Lindgren, Cecilia M., Morris, Andrew P., Meyre, David, Scherag, André, McCarthy, Mark I., Speliotes, Elizabeth K., North, Kari E., Loos, Ruth J.F., Ingelsson, Erik, and Hirschhorn, Joel

Published
2013
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37. Copy number variants and placental abnormalities in stillborn fetuses: A secondary analysis of the Stillbirth Collaborative Research Network study

Author

Workalemahu, Tsegaselassie, primary, Dalton, Susan, additional, Allshouse, Amanda, additional, Carey, Andrew Z., additional, Page, Jessica M., additional, Blue, Nathan R., additional, Thorsten, Vanessa, additional, Goldenberg, Robert L., additional, Pinar, Halit, additional, Reddy, Uma M., additional, and Silver, Robert M., additional

Published
2022
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42. Familial aggregation of stillbirth: A pedigree analysis of a matched case–control study.

Author

Workalemahu, Tsegaselassie, Page, Jessica M., Meeks, Huong, Yu, Zhe, Guinto, Emily, Fraser, Alison, Varner, Michael W., Theilen, Lauren H., Quinlan, Aaron, Coon, Hilary, Enquobahrie, Daniel A., Ananth, Cande V., Tekola‐Ayele, Fasil, Jorde, Lynn B., and Silver, Robert M.

Subjects
*STILLBIRTH, *FETAL death, *CASE-control method, *GENEALOGY, *LOGISTIC regression analysis, *FETAL movement
Abstract

Objective: To determine whether stillbirth aggregates in families and quantify its familial risk using extended pedigrees. Design: State‐wide matched case–control study. Setting Utah, United States. Population Stillbirth cases (n = 9404) and live birth controls (18 808) between 1978 and 2019. Methods: Using the Utah Population Database, a population‐based genealogical resource linked with state fetal death and birth records, we identified high‐risk pedigrees with excess familial aggregation of stillbirth using the Familial Standardised Incidence Ratio (FSIR). Stillbirth odds ratio (OR) for first‐degree relatives (FDR), second‐degree relatives (SDR) and third‐degree relatives (TDR) of parents with a stillbirth (affected) and live birth (unaffected) were estimated using logistic regression models. Main outcome measures: Familial aggregation estimated using FSIR, and stillbirth OR estimated for FDR, SDR and TDR of affected and unaffected parents using logistic regression models. Results: We identified 390 high‐risk pedigrees with evidence for excess familial aggregation (FSIR ≥2.00; P‐value <0.05). FDRs, SDRs and TDRs of affected parents had 1.14‐fold (95% confidence interval [CI]: 1.04–1.26), 1.22‐fold (95% CI 1.11–1.33) and 1.15‐fold (95% CI 1.08–1.21) higher stillbirth odds compared with FDRs, SDRs and TDRs of unaffected parents, respectively. Parental sex‐specific analyses showed male FDRs, SDRs and TDRs of affected fathers had 1.22‐fold (95% CI 1.02–1.47), 1.38‐fold (95% CI 1.17–1.62) and 1.17‐fold (95% CI 1.05–1.30) higher stillbirth odds compared with those of unaffected fathers, respectively. FDRs, SDRs and TDRs of affected mothers had 1.12‐fold (95% CI 0.98–1.28), 1.09‐fold (95% CI 0.96–1.24) and 1.15‐fold (95% CI 1.06–1.24) higher stillbirth odds compared with those of unaffected mothers, respectively. Conclusions: We provide evidence for familial aggregation of stillbirth. Our findings warrant investigation into genes associated with stillbirth and underscore the need to design large‐scale studies to determine the genetic architecture of stillbirth. Linked article:This article is commented on by Matthew A. Shear, pp. 463 in this issue. To view this mini commentary visit https://doi.org/10.1111/1471-0528.17365 [ABSTRACT FROM AUTHOR]

Published
2023
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46. Maternal-fetal genetic interactions, imprinting, and risk of placental abruption.

Author

Workalemahu, Tsegaselassie, Enquobahrie, Daniel A., Gelaye, Bizu, Tadesse, Mahlet G., Sanchez, Sixto E., Tekola-Ayele, Fasil, Hajat, Anjum, Thornton, Timothy A., Ananth, Cande V., and Williams, Michelle A.

Subjects
*ABRUPTIO placentae, *CALMODULIN, *GENOMIC imprinting, *SINGLE nucleotide polymorphisms, *CALCIUM-dependent protein kinase, *GENETIC variation, *LIKELIHOOD ratio tests
Abstract

Background: Maternal genetic variations, including variations in mitochondrial biogenesis (MB) and oxidative phosphorylation (OP), are associated with placental abruption (PA). However, the role of maternal-fetal genetic interactions (MFGI) and parent-of-origin (imprinting) effects in PA remain unknown. Objective: To investigate MFGI in MB-OP, and imprinting effects in relation to risk of PA. Methods: Among Peruvian mother-infant pairs (503 PA cases and 1052 controls), independent single nucleotide polymorphisms (SNPs), with linkage-disequilibrium coefficient <0.80, were selected to characterize genetic variations in MB-OP (78 SNPs in 24 genes) and imprinted genes (2713 SNPs in 73 genes). For each MB-OP SNP, four multinomial models corresponding to fetal allele effect, maternal allele effect, maternal and fetal allele additive effect, and maternal-fetal allele interaction effect were fit under Hardy-Weinberg equilibrium, random mating, and rare disease assumptions. The Bayesian information criterion (BIC) was used for model selection. For each SNP in imprinted genes, imprinting effect was tested using a likelihood ratio test. Bonferroni corrections were used to determine statistical significance (p-value < 6.4e-4 for MFGI and p-value < 1.8e-5 for imprinting). Abruption cases were more likely to experience preeclampsia, have shorter gestational age, and deliver infants with lower birthweight compared with controls. Models with MFGI effects provided improved fit than models with only maternal and fetal genotype main effects for SNP rs12530904 (p-value = 1.2e-04) in calcium/calmodulin-dependent protein kinase [CaM kinase] II beta (CAMK2B), and, SNP rs73136795 (p-value = 1.9e-04) in peroxisome proliferator-activated receptor-gamma (PPARG), both MB genes. We identified 320 SNPs in 45 maternally-imprinted genes (including potassium voltage-gated channel subfamily Q member 1 [KCNQ1], neurotrimin [NTM], and, ATPase phospholipid transporting 10 A [ATP10A]) associated with abruption. Top hits included rs2012323 (p-value = 1.6E-16) and rs12221520 (p-value1.3e-13) in KCNQ1, rs8036892 (p-value = 9.3E-17) and rs188497582 in ATP10A, rs12589854 (p-value = 2.9E-11) and rs80203467 (p-value = 4.6e-11) in maternally expressed 8, small nucleolar RNA host (MEG8), and rs138281088 in solute carrier family 22 member 2 (SLC22A2) (p-value = 6.8e-9). We identified novel PA-related maternal-fetal MB gene interactions and imprinting effects that highlight the role of the fetus in PA risk development. Findings can inform mechanistic investigations to understand the pathogenesis of PA. [ABSTRACT FROM AUTHOR]

Published
2022
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47. Genome-wide analysis of BMI in adolescents and young adults reveals additional insight into the effects of genetic loci over the life course

Author

Graff, Mariaelisa, Ngwa, Julius S., Workalemahu, Tsegaselassie, Homuth, Georg, Schipf, Sabine, Teumer, Alexander, Völzke, Henry, Wallaschofski, Henri, Abecasis, Goncalo R., Edward, Lakatta, Francesco, Cucca, Sanna, Serena, Scheet, Paul, Schlessinger, David, Sidore, Carlo, Xiao, Xiangjun, Wang, Zhaoming, Chanock, Stephen J., Jacobs, Kevin B., Hayes, Richard B., Hu, Frank, Van Dam, Rob M., Crout, Richard J., Marazita, Mary L., Shaffer, John R, Atwood, Larry D., Fox, Caroline S., Heard-Costa, Nancy L., White, Charles, Choh, Audrey C., Czerwinski, Stefan A., Demerath, Ellen W., Dyer, Thomas D., Towne, Bradford, Amin, Najaf, Oostra, Ben A., Van Duijn, Cornelia M., Zillikens, M. Carola, Esko, Tõnu, Nelis, Mari, Nikopensius, Tit, Metspalu, Andres, Strachan, David P., Monda, Keri, Qi, Lu, North, Kari E., Cupples, L. Adrienne, Gordon-Larsen, Penny, and Berndt, Sonja I.

Published
2013
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