82 results on '"Ruth, KS"'
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2. Influence of family history on penetrance of hereditary cancers in a population setting
- Author
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Jackson, L, primary, Weedon, MN, additional, Harrison, JW, additional, Wood, AR, additional, Ruth, KS, additional, Tyrrell, J, additional, and Wright, CF, additional
- Published
- 2022
- Full Text
- View/download PDF
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3. Genetic association study of childhood aggression across raters, instruments, and age
- Author
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Nicholas G. Martin, S. Alexandra Burt, Louise Arseneault, Fazil Aliev, Luke M. Evans, Hill F. Ip, Beate St Pourcain, Michel G. Nivard, William E. Copeland, Rebecca K. Vinding, Scott Gordon, Koen Bolhuis, Christian J. Hopfer, Gun Peggy Knudsen, Stefan Johansson, Avshalom Caspi, Richard Border, Chandra A. Reynolds, Pål R. Njølstad, Liisa Keltikangas-Järvinen, Dorret I. Boomsma, Klaus Bønnelykke, Teemu Palviainen, Marta Ribasés, Alina Rodriguez, Catharina A. Hartman, Ilkka Seppälä, Christel M. Middeldorp, Rosa Bosch, Jan Haavik, Gail M. Williams, Andrea G. Allegrini, Ruth Ks, John R. B. Perry, Hadi Zafarmand, Chang Jiang, Elizabeth J. Costello, Camiel M. van der Laan, Olli T. Raitakari, Miquel Casas, Isabell Brikell, William G. Iacono, Jaakko Kaprio, John K. Hewitt, Andrew C. Heath, Eero Vuoksimaa, Xiaoran Tong, Gemma Español, Erik A. Ehli, Richie Poulton, Gareth E. Davies, Albertine J. Oldehinkel, Hans Bisgaard, Naomi R. Wray, Ted Reichborn-Kjennerud, Robert Plomin, Michael C. Stallings, Qing Lu, Jackob M. Najman, Daniel E. Adkins, Yi Lu, Harold Snieder, Sally J. Wadsworth, Alexander Neumann, Alexandra Havdahl, Karen Sugden, Kelly L. Klump, Andrew Smolen, Henrik Larsson, Toos C. E. M. van Beijsterveldt, Kenneth Krauter, Tarunveer S. Ahluwalia, Tellervo Korhonen, Andrey A. Shabalin, Joachim Heinrich, Anke R. Hammerschlag, Shelby Marrington, Lærke Sass, Pamela A. F. Madden, Henning Tiemeier, Tanja Vrijkotte, Paul Lichtenstein, Terho Lehtimäki, Ville Karhunen, Cristina Sánchez-Mora, Robin P. Corley, Anna A. E. Vinkhuyzen, Richard J. Rose, Per Magnus, Sabrina Llop, Ilja M. Nolte, S.A. Brown, Christian Hakulinen, Anjali K. Henders, Marie Standl, Silvia Alemany, Gretchen R.B. Saunders, Jouke-Jan Hottenga, Eveline L. de Zeeuw, Meike Bartels, Elisabeth Thiering, José J. Morosoli, Fiona A. Hagenbeek, Laura Pulkki-Råback, Frank C. Verhulst, Martin A. Kennedy, Craig E. Pennell, Eva Krapohl, Kaili Rimfeld, Tetyana Zayats, Lucía Colodro-Conde, Judith B.M. Ensink, André G. Uitterlinden, Natalia Vilor-Tejedor, Felix R. Day, Jennifer R. Harris, George Davey Smith, Qi Chen, Sebastian Lundström, Marjo-Riitta Järvelin, Alyce M. Whipp, Katrina L. Grasby, L. John Horwood, John Pearson, Judy L. Silberg, Paula Rovira, Hermine H. Maes, Carol A. Wang, Roseann E. Peterson, Tamara L. Wall, Andrew J. O. Whitehouse, Maria-Jose Lopez-Espinosa, Najaf Amin, Jess Tyrrell, Danielle M. Dick, Sarah E. Medland, Allison L. Miller, Øyvind Helgeland, Josep Antoni Ramos Quiroga, Joseph M. Boden, Abdullah Mamun, James Scott, María Soler Artigas, Joseph A. Prinz, Lindon J. Eaves, Terrie E. Moffitt, Matt McGue, Jordi Sunyer, Joanna Martin, Tampere University, Clinical Medicine, Department of Clinical Chemistry, Apollo-University Of Cambridge Repository, Ip, Hill F [0000-0003-1991-5019], Sánchez-Mora, Cristina [0000-0003-4211-1107], Nolte, Ilja M [0000-0001-5047-4077], St Pourcain, Beate [0000-0002-4680-3517], Palviainen, Teemu [0000-0002-7847-8384], Colodro-Conde, Lucía [0000-0002-9004-364X], Gordon, Scott [0000-0001-7623-328X], Aliev, Fazil [0000-0001-8357-4699], Karhunen, Ville [0000-0001-6064-1588], Border, Richard [0000-0002-6293-2968], Ahluwalia, Tarunveer S [0000-0002-7464-3354], Day, Felix R [0000-0003-3789-7651], Hottenga, Jouke-Jan [0000-0002-5668-2368], Rimfeld, Kaili [0000-0001-5139-065X], Lu, Yi [0000-0001-9933-3654], Soler Artigas, María [0000-0002-3213-1107], Bosch, Rosa [0000-0002-7596-183X], Ramos Quiroga, Josep Antoni [0000-0003-1622-0350], Neumann, Alexander [0000-0001-6653-3203], Grasby, Katrina [0000-0001-8539-0228], Middeldorp, Christel [0000-0002-6218-0428], Evans, Luke M [0000-0002-7458-1720], Alemany, Silvia [0000-0002-7925-6767], Sass, Lærke [0000-0002-5217-7014], Ruth, Kate [0000-0003-4966-9170], Ehli, Erik A [0000-0002-7865-3015], Hagenbeek, Fiona A [0000-0002-8773-0430], Snieder, Harold [0000-0003-1949-2298], Uitterlinden, André G [0000-0002-7276-3387], Haavik, Jan [0000-0001-7865-2808], Johansson, Stefan [0000-0002-2298-7008], Knudsen, Gun Peggy S [0000-0002-6193-4291], Njolstad, Pal Rasmus [0000-0003-0304-6728], Rodriguez, Alina [0000-0003-1209-8802], Brown, Sandy [0000-0001-8780-0323], Miller, Allison [0000-0003-3816-2251], Keltikangas-Järvinen, Liisa [0000-0002-7977-3852], Havdahl, Alexandra [0000-0002-9268-0423], Perry, John RB [0000-0001-6483-3771], Lehtimäki, Terho [0000-0002-2555-4427], Arseneault, Louise [0000-0002-2938-2191], Boden, Joseph [0000-0003-1502-1608], Pearson, John [0000-0001-5607-4517], Kennedy, Martin [0000-0002-6445-8526], Poulton, Richie [0000-0002-1052-4583], Copeland, William E [0000-0002-1348-7781], Wray, Naomi [0000-0001-7421-3357], Järvelin, Marjo-Riitta [0000-0002-2149-0630], McGue, Matt [0000-0002-5580-1433], Pennell, Craig E [0000-0002-0937-6165], Dick, Danielle M [0000-0002-1636-893X], Martin, Nicholas G [0000-0003-4069-8020], Medland, Sarah E [0000-0003-1382-380X], Kaprio, Jaakko [0000-0002-3716-2455], Tiemeier, Henning [0000-0002-4395-1397], Davey Smith, George [0000-0002-1407-8314], Oldehinkel, Albertine J [0000-0003-3925-3913], Ribasés, Marta [0000-0003-1039-1116], Lichtenstein, Paul [0000-0003-3037-5287], Plomin, Robert [0000-0002-0756-3629], Bartels, Meike [0000-0002-9667-7555], Nivard, Michel G [0000-0003-2015-1888], Boomsma, Dorret I [0000-0002-7099-7972], Apollo - University of Cambridge Repository, Life Course Epidemiology (LCE), Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Child and Adolescent Psychiatry / Psychology, Epidemiology, Internal Medicine, Institute for Molecular Medicine Finland, Genetic Epidemiology, Helsinki Institute of Life Science HiLIFE, University of Helsinki, Tellervo Korhonen / Principal Investigator, Cognitive and Brain Aging, Faculty Common Matters (Faculty of Medicine), Medicum, Doctoral Programme in Cognition, Learning, Instruction and Communication, Department of Psychology and Logopedics, Helsinki Inequality Initiative (INEQ), Faculty Common Matters (Faculty of Education), Psychosocial factors and health, Behavioural Sciences, Department of Public Health, Adult Psychiatry, Epidemiology and Data Science, APH - Aging & Later Life, APH - Methodology, ARD - Amsterdam Reproduction and Development, Graduate School, Child Psychiatry, ACS - Pulmonary hypertension & thrombosis, ANS - Cellular & Molecular Mechanisms, ANS - Compulsivity, Impulsivity & Attention, Public and occupational health, APH - Health Behaviors & Chronic Diseases, Institut Català de la Salut, [Ip HF] Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands. [van der Laan CM] Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands. Netherlands Institute for the Study of Crime and Law Enforcement, Amsterdam, The Netherlands. [Krapohl EML] Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK. [Brikell I] Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. [Sánchez-Mora C, Soler Artigas M, Rovira P, Ribasés M] Servei de Psiquiatria, Vall d’Hebron Hospital Universitari, Barcelona, Spain. Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Barcelona, Spain. Unitat de Genètica Psiquiàtrica, Grup de Recerca en Psiquiatria, Salut Mental i Addicció, Vall d’Hebron Institut de Recerca (VHIR), Barcelona, Spain. Universitat Autònoma de Barcelona, Bellaterra, Spain. [Nolte IM] Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. [Bosch R] Servei de Psiquiatria, Vall d’Hebron Hospital Universitari, Barcelona, Spain. Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Barcelona, Spain. Servei de Psiquiatria i Medicina Legal, Universitat Autònoma de Barcelona, Bellaterra, Spain. [Español G] Servei de Psiquiatria, Vall d’Hebron Hospital Universitari, Barcelona, Spain. [Ramos Quiroga JA, Ribasés M] Servei de Psiquiatria, Vall d’Hebron Hospital Universitari, Barcelona, Spain. Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Barcelona, Spain. Unitat de Genètica Psiquiàtrica, Grup de Recerca en Psiquiatria, Salut Mental i Addicció, Vall d’Hebron Institut de Recerca (VHIR), Barcelona, Spain. Universitat Autònoma de Barcelona, Bellaterra, Spain. Servei de Psiquiatria i Medicina Legal, Universitat Autònoma de Barcelona, Bellaterra, Spain, Vall d'Hebron Barcelona Hospital Campus, Biological Psychology, APH - Personalized Medicine, APH - Mental Health, Amsterdam Reproduction & Development, Perry, John R B [0000-0001-6483-3771], Ip, Hill F. [0000-0003-1991-5019], Nolte, Ilja M. [0000-0001-5047-4077], Ahluwalia, Tarunveer S. [0000-0002-7464-3354], Day, Felix R. [0000-0003-3789-7651], Evans, Luke M. [0000-0002-7458-1720], Ehli, Erik A. [0000-0002-7865-3015], Hagenbeek, Fiona A. [0000-0002-8773-0430], Uitterlinden, André G. [0000-0002-7276-3387], Knudsen, Gun Peggy S. [0000-0002-6193-4291], Perry, John R. B. [0000-0001-6483-3771], Copeland, William E. [0000-0002-1348-7781], Pennell, Craig E. [0000-0002-0937-6165], Dick, Danielle M. [0000-0002-1636-893X], Martin, Nicholas G. [0000-0003-4069-8020], Medland, Sarah E. [0000-0003-1382-380X], Oldehinkel, Albertine J. [0000-0003-3925-3913], Nivard, Michel G. [0000-0003-2015-1888], and Boomsma, Dorret I. [0000-0002-7099-7972] more...
- Subjects
0301 basic medicine ,DISORDER ,45/43 ,Genome-wide association study ,3124 Neurology and psychiatry ,0302 clinical medicine ,Child ,Psychiatry ,0303 health sciences ,trastornos mentales [PSIQUIATRÍA Y PSICOLOGÍA] ,HERITABILITY ,Mental Disorders ,Cognition ,Genomics ,Explained variation ,Justice and Strong Institutions ,Aggression ,Psychiatry and Mental health ,Meta-analysis ,ADOLESCENCE ,Child, Preschool ,conducta y mecanismos de la conducta::conducta::síntomas conductuales::agresión [PSIQUIATRÍA Y PSICOLOGÍA] ,631/208/212 ,Female ,Biological psychiatry ,medicine.symptom ,Life Sciences & Biomedicine ,Investigative Techniques::Genetic Techniques::Genetic Association Studies [ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT] ,BEHAVIOR ,RC321-571 ,Childhood aggression ,Clinical psychology ,SDG 16 - Peace ,Adolescent ,Mental Disorders [PSYCHIATRY AND PSYCHOLOGY] ,Neurosciences. Biological psychiatry. Neuropsychiatry ,Single-nucleotide polymorphism ,Biology ,3121 Internal medicine ,Malalties mentals - Aspectes genètics ,Genetic correlation ,Article ,1117 Public Health and Health Services ,Cellular and Molecular Neuroscience ,03 medical and health sciences ,631/477/2811 ,SDG 3 - Good Health and Well-being ,Human behaviour ,medicine ,SNP ,Humans ,GENOME-WIDE ASSOCIATION ,Biological Psychiatry ,Genetic Association Studies ,030304 developmental biology ,Genetic association ,Retrospective Studies ,técnicas de investigación::técnicas genéticas::estudios de asociación genética [TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS] ,Science & Technology ,SDG 16 - Peace, Justice and Strong Institutions ,Infant ,Behavior and Behavior Mechanisms::Behavior::Behavioral Symptoms::Aggression [PSYCHIATRY AND PSYCHOLOGY] ,1103 Clinical Sciences ,Agressivitat en els infants ,Heritability ,030104 developmental biology ,1701 Psychology ,ORIGINS ,Research Programm of Donders Centre for Neuroscience ,3111 Biomedicine ,TRAJECTORIES ,030217 neurology & neurosurgery ,Demography ,Genome-Wide Association Study - Abstract
Childhood aggressive behavior (AGG) has a substantial heritability of around 50%. Here we present a genome-wide association meta-analysis (GWAMA) of childhood AGG, in which all phenotype measures across childhood ages from multiple assessors were included. We analyzed phenotype assessments for a total of 328 935 observations from 87 485 children aged between 1.5 and 18 years, while accounting for sample overlap. We also meta-analyzed within subsets of the data, i.e., within rater, instrument and age. SNP-heritability for the overall meta-analysis (AGGoverall) was 3.31% (SE = 0.0038). We found no genome-wide significant SNPs for AGGoverall. The gene-based analysis returned three significant genes: ST3GAL3 (P = 1.6E–06), PCDH7 (P = 2.0E–06), and IPO13 (P = 2.5E–06). All three genes have previously been associated with educational traits. Polygenic scores based on our GWAMA significantly predicted aggression in a holdout sample of children (variance explained = 0.44%) and in retrospectively assessed childhood aggression (variance explained = 0.20%). Genetic correlations (rg) among rater-specific assessment of AGG ranged from rg = 0.46 between self- and teacher-assessment to rg = 0.81 between mother- and teacher-assessment. We obtained moderate-to-strong rgs with selected phenotypes from multiple domains, but hardly with any of the classical biomarkers thought to be associated with AGG. Significant genetic correlations were observed with most psychiatric and psychological traits (range $$\left| {r_g} \right|$$ r g : 0.19–1.00), except for obsessive-compulsive disorder. Aggression had a negative genetic correlation (rg = ~−0.5) with cognitive traits and age at first birth. Aggression was strongly genetically correlated with smoking phenotypes (range $$\left| {r_g} \right|$$ r g : 0.46–0.60). The genetic correlations between aggression and psychiatric disorders were weaker for teacher-reported AGG than for mother- and self-reported AGG. The current GWAMA of childhood aggression provides a powerful tool to interrogate the rater-specific genetic etiology of AGG. more...
- Published
- 2021
- Full Text
- View/download PDF
4. Genetic insights into biological mechanisms governing human ovarian ageing
- Author
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Ruth, KS, Day, FR, Hussain, J, Martinez-Marchal, A, Aiken, CE, Azad, A, Thompson, DJ, Knoblochova, L, Abe, H, Tarry-Adkins, JL, Gonzalez, JM, Fontanillas, P, Claringbould, A, Bakker, OB, Sulem, P, Walters, RG, Terao, C, Turon, S, Horikoshi, M, Lin, K, Onland-Moret, NC, Sankar, A, Hertz, EPT, Timshel, PN, Shukla, V, Borup, R, Olsen, KW, Aguilera, P, Ferrer-Roda, M, Huang, Y, Stankovic, S, Timmers, PRHJ, Ahearn, TU, Alizadeh, BZ, Naderi, E, Andrulis, IL, Arnold, AM, Aronson, KJ, Augustinsson, A, Bandinelli, S, Barbieri, CM, Beaumont, RN, Becher, H, Beckmann, MW, Benonisdottir, S, Bergmann, S, Bochud, M, Boerwinkle, E, Bojesen, SE, Bolla, MK, Boomsma, DI, Bowker, N, Brody, JA, Broer, L, Buring, JE, Campbell, A, Campbell, H, Castelao, JE, Catamo, E, Chanock, SJ, Chenevix-Trench, G, Ciullo, M, Corre, T, Couch, FJ, Cox, A, Crisponi, L, Cross, SS, Cucca, F, Czene, K, Smith, GD, de Geus, EJCN, de Mutsert, R, De Vivo, I, Demerath, EW, Dennis, J, Dunning, AM, Dwek, M, Eriksson, M, Esko, T, Fasching, PA, Faul, JD, Ferrucci, L, Franceschini, N, Frayling, TM, Gago-Dominguez, M, Mezzavilla, M, Garcia-Closas, M, Gieger, C, Giles, GG, Grallert, H, Gudbjartsson, DF, Gudnason, V, Guenel, P, Haiman, CA, Hakansson, N, Hall, P, Hayward, C, He, C, He, W, Heiss, G, Hoffding, MK, Hopper, JL, Hottenga, JJ, Hu, F, Hunter, D, Ikram, MA, Jackson, RD, Joaquim, MDR, John, EM, Joshi, PK, Karasik, D, Kardia, SLR, Kartsonaki, C, Karlsson, R, Kitahara, CM, Kolcic, I, Kooperberg, C, Kraft, P, Kurian, AW, Kutalik, Z, La Bianca, M, LaChance, G, Langenberg, C, Launer, LJ, Laven, JSE, Lawlor, DA, Le Marchand, L, Li, J, Lindblom, A, Lindstrom, S, Lindstrom, T, Linet, M, Liu, Y, Liu, S, Luan, J, Magi, R, Magnusson, PKE, Mangino, M, Mannermaa, A, Marco, B, Marten, J, Martin, NG, Mbarek, H, McKnight, B, Medland, SE, Meisinger, C, Meitinger, T, Menni, C, Metspalu, A, Milani, L, Milne, RL, Montgomery, GW, Mook-Kanamori, DO, Mulas, A, Mulligan, AM, Murray, A, Nalls, MA, Newman, A, Noordam, R, Nutile, T, Nyholt, DR, Olshan, AF, Olsson, H, Painter, JN, Patel, AV, Pedersen, NL, Perjakova, N, Peters, A, Peters, U, Pharoah, PDP, Polasek, O, Porcu, E, Psaty, BM, Rahman, I, Rennert, G, Rennert, HS, Ridker, PM, Ring, SM, Robino, A, Rose, LM, Rosendaal, FR, Rossouw, J, Rudan, I, Rueedi, R, Ruggiero, D, Sala, CF, Saloustros, E, Sandler, DP, Sanna, S, Sawyer, EJ, Sarnowski, C, Schlessinger, D, Schmidt, MK, Schoemaker, MJ, Schraut, KE, Scott, C, Shekari, S, Shrikhande, A, Smith, AV, Smith, BH, Smith, JA, Sorice, R, Southey, MC, Spector, TD, Spinelli, JJ, Stampfer, M, Stoeckl, D, van Meurs, JBJ, Strauch, K, Styrkarsdottir, U, Swerdlow, AJ, Tanaka, T, Teras, LR, Teumer, A, thorsteinsdottir, U, Timpson, NJ, Toniolo, D, Traglia, M, Troester, MA, Truong, T, Tyrrell, J, Uitterlinden, AG, Ulivi, S, Vachon, CM, Vitart, V, Voelker, U, Vollenweider, P, Voelzke, H, Wang, Q, Wareham, NJ, Weinberg, CR, Weir, DR, Wilcox, AN, van Dijk, KW, Willemsen, G, Wilson, JF, Wolffenbuttel, BHR, Wolk, A, Wood, AR, Zhao, W, Zygmunt, M, Chen, Z, Li, L, Franke, L, Burgess, S, Deelen, P, Pers, TH, Grondahl, ML, Andersen, CY, Pujol, A, Lopez-Contreras, AJ, Daniel, JA, Stefansson, K, Chang-Claude, J, van der Schouw, YT, Lunetta, KL, Chasman, DI, Easton, DF, Visser, JA, Ozanne, SE, Namekawa, SH, Solc, P, Murabito, JM, Ong, KK, Hoffmann, ER, Roig, I, Perry, JRB, Ruth, KS, Day, FR, Hussain, J, Martinez-Marchal, A, Aiken, CE, Azad, A, Thompson, DJ, Knoblochova, L, Abe, H, Tarry-Adkins, JL, Gonzalez, JM, Fontanillas, P, Claringbould, A, Bakker, OB, Sulem, P, Walters, RG, Terao, C, Turon, S, Horikoshi, M, Lin, K, Onland-Moret, NC, Sankar, A, Hertz, EPT, Timshel, PN, Shukla, V, Borup, R, Olsen, KW, Aguilera, P, Ferrer-Roda, M, Huang, Y, Stankovic, S, Timmers, PRHJ, Ahearn, TU, Alizadeh, BZ, Naderi, E, Andrulis, IL, Arnold, AM, Aronson, KJ, Augustinsson, A, Bandinelli, S, Barbieri, CM, Beaumont, RN, Becher, H, Beckmann, MW, Benonisdottir, S, Bergmann, S, Bochud, M, Boerwinkle, E, Bojesen, SE, Bolla, MK, Boomsma, DI, Bowker, N, Brody, JA, Broer, L, Buring, JE, Campbell, A, Campbell, H, Castelao, JE, Catamo, E, Chanock, SJ, Chenevix-Trench, G, Ciullo, M, Corre, T, Couch, FJ, Cox, A, Crisponi, L, Cross, SS, Cucca, F, Czene, K, Smith, GD, de Geus, EJCN, de Mutsert, R, De Vivo, I, Demerath, EW, Dennis, J, Dunning, AM, Dwek, M, Eriksson, M, Esko, T, Fasching, PA, Faul, JD, Ferrucci, L, Franceschini, N, Frayling, TM, Gago-Dominguez, M, Mezzavilla, M, Garcia-Closas, M, Gieger, C, Giles, GG, Grallert, H, Gudbjartsson, DF, Gudnason, V, Guenel, P, Haiman, CA, Hakansson, N, Hall, P, Hayward, C, He, C, He, W, Heiss, G, Hoffding, MK, Hopper, JL, Hottenga, JJ, Hu, F, Hunter, D, Ikram, MA, Jackson, RD, Joaquim, MDR, John, EM, Joshi, PK, Karasik, D, Kardia, SLR, Kartsonaki, C, Karlsson, R, Kitahara, CM, Kolcic, I, Kooperberg, C, Kraft, P, Kurian, AW, Kutalik, Z, La Bianca, M, LaChance, G, Langenberg, C, Launer, LJ, Laven, JSE, Lawlor, DA, Le Marchand, L, Li, J, Lindblom, A, Lindstrom, S, Lindstrom, T, Linet, M, Liu, Y, Liu, S, Luan, J, Magi, R, Magnusson, PKE, Mangino, M, Mannermaa, A, Marco, B, Marten, J, Martin, NG, Mbarek, H, McKnight, B, Medland, SE, Meisinger, C, Meitinger, T, Menni, C, Metspalu, A, Milani, L, Milne, RL, Montgomery, GW, Mook-Kanamori, DO, Mulas, A, Mulligan, AM, Murray, A, Nalls, MA, Newman, A, Noordam, R, Nutile, T, Nyholt, DR, Olshan, AF, Olsson, H, Painter, JN, Patel, AV, Pedersen, NL, Perjakova, N, Peters, A, Peters, U, Pharoah, PDP, Polasek, O, Porcu, E, Psaty, BM, Rahman, I, Rennert, G, Rennert, HS, Ridker, PM, Ring, SM, Robino, A, Rose, LM, Rosendaal, FR, Rossouw, J, Rudan, I, Rueedi, R, Ruggiero, D, Sala, CF, Saloustros, E, Sandler, DP, Sanna, S, Sawyer, EJ, Sarnowski, C, Schlessinger, D, Schmidt, MK, Schoemaker, MJ, Schraut, KE, Scott, C, Shekari, S, Shrikhande, A, Smith, AV, Smith, BH, Smith, JA, Sorice, R, Southey, MC, Spector, TD, Spinelli, JJ, Stampfer, M, Stoeckl, D, van Meurs, JBJ, Strauch, K, Styrkarsdottir, U, Swerdlow, AJ, Tanaka, T, Teras, LR, Teumer, A, thorsteinsdottir, U, Timpson, NJ, Toniolo, D, Traglia, M, Troester, MA, Truong, T, Tyrrell, J, Uitterlinden, AG, Ulivi, S, Vachon, CM, Vitart, V, Voelker, U, Vollenweider, P, Voelzke, H, Wang, Q, Wareham, NJ, Weinberg, CR, Weir, DR, Wilcox, AN, van Dijk, KW, Willemsen, G, Wilson, JF, Wolffenbuttel, BHR, Wolk, A, Wood, AR, Zhao, W, Zygmunt, M, Chen, Z, Li, L, Franke, L, Burgess, S, Deelen, P, Pers, TH, Grondahl, ML, Andersen, CY, Pujol, A, Lopez-Contreras, AJ, Daniel, JA, Stefansson, K, Chang-Claude, J, van der Schouw, YT, Lunetta, KL, Chasman, DI, Easton, DF, Visser, JA, Ozanne, SE, Namekawa, SH, Solc, P, Murabito, JM, Ong, KK, Hoffmann, ER, Roig, I, and Perry, JRB more...
- Abstract
Reproductive longevity is essential for fertility and influences healthy ageing in women1,2, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations3. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease. more...
- Published
- 2021
5. Assessing the analytical validity of SNP-chips for detecting very rare pathogenic variants: implications for direct-to-consumer genetic testing
- Author
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Leigh Jackson, Jessica Tyrrell, Michael N. Weedon, Andrew T. Hattersley, James W Harrison, Caroline F. Wright, and Ruth Ks
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Personal Genome Project ,medicine.diagnostic_test ,Genotype ,medicine ,Computational biology ,Biology ,Genotyping ,Biobank ,Genome ,SNP genotyping ,Cancer registry ,Genetic testing - Abstract
ObjectivesTo determine the analytical validity of SNP-chips for genotyping very rare genetic variants.DesignRetrospective study using data from two publicly available resources, the UK Biobank and the Personal Genome Project.SettingResearch biobanks and direct-to-consumer genetic testing in the UK and USA.Participants49,908 individuals recruited to UK Biobank, and 21 individuals who purchased consumer genetic tests and shared their data online via the Personal Genomes Project.Main outcome measuresWe assessed the analytical validity of genotypes from SNP-chips (index test) with sequencing data (reference standard). We evaluated the genotyping accuracy of the SNP-chips and split the results by variant frequency. We went on to select rare pathogenic variants in the BRCA1 and BRCA2 genes as an exemplar for detailed analysis of clinically-actionable variants in UK Biobank, and assessed BRCA-related cancers (breast, ovarian, prostate and pancreatic) in participants using cancer registry data.ResultsSNP-chip genotype accuracy is high overall; sensitivity, specificity and precision are all >99% for 108,574 common variants directly genotyped by the UK Biobank SNP-chips. However, the likelihood of a true positive result reduces dramatically with decreasing variant frequency; for variants with a frequency BRCA1 and BRCA2 genes, the overall performance metrics of the SNP-chips in UK Biobank are sensitivity 34.6%, specificity 98.3% and precision 4.2%. Rates of BRCA-related cancers in individuals in UK Biobank with a positive SNP-chip result are similar to age-matched controls (OR 1.28, P=0.07, 95% CI: 0.98 to 1.67), while sequence-positive individuals have a significantly increased risk (OR 3.73, P=3.5×10−12, 95% CI: 2.57 to 5.40).ConclusionSNP-chips are extremely unreliable for genotyping very rare pathogenic variants and should not be used to guide health decisions without validation.SUMMARY BOXSection 1: What is already known on this topicSNP-chips are an accurate and affordable method for genotyping common genetic variants across the genome. They are often used by direct-to-consumer (DTC) genetic testing companies and research studies, but there several case reports suggesting they perform poorly for genotyping rare genetic variants when compared with sequencing.Section 2: What this study addsOur study confirms that SNP-chips are highly inaccurate for genotyping rare, clinically-actionable variants. Using large-scale SNP-chip and sequencing data from UK Biobank, we show that SNP-chips have a very low precision of more...
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- 2019
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6. Use of SNP chips to detect rare pathogenic variants: retrospective, population based diagnostic evaluation
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Jamie W. Harrison, Caroline F. Wright, Michael N. Weedon, Jessica Tyrrell, Andrew T. Hattersley, Leigh Jackson, and Ruth Ks
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Adult ,Male ,Oncology ,medicine.medical_specialty ,Genotyping Techniques ,Genes, BRCA2 ,Population ,Genes, BRCA1 ,Breast Neoplasms ,Corrections ,Polymorphism, Single Nucleotide ,03 medical and health sciences ,Predictive Value of Tests ,Internal medicine ,medicine ,False positive paradox ,Humans ,False Positive Reactions ,Genetic Testing ,Registries ,education ,False Negative Reactions ,Genotyping ,Aged ,Oligonucleotide Array Sequence Analysis ,Retrospective Studies ,030304 developmental biology ,Ovarian Neoplasms ,0303 health sciences ,education.field_of_study ,business.industry ,Research ,030305 genetics & heredity ,High-Throughput Nucleotide Sequencing ,Prostatic Neoplasms ,Sequence Analysis, DNA ,General Medicine ,Odds ratio ,Middle Aged ,Biobank ,SNP genotyping ,Pancreatic Neoplasms ,Predictive value of tests ,Female ,business - Abstract
Objective To determine whether the sensitivity and specificity of SNP chips are adequate for detecting rare pathogenic variants in a clinically unselected population. Design Retrospective, population based diagnostic evaluation. Participants 49 908 people recruited to the UK Biobank with SNP chip and next generation sequencing data, and an additional 21 people who purchased consumer genetic tests and shared their data online via the Personal Genome Project. Main outcome measures Genotyping (that is, identification of the correct DNA base at a specific genomic location) using SNP chips versus sequencing, with results split by frequency of that genotype in the population. Rare pathogenic variants in the BRCA1 and BRCA2 genes were selected as an exemplar for detailed analysis of clinically actionable variants in the UK Biobank, and BRCA related cancers (breast, ovarian, prostate, and pancreatic) were assessed in participants through use of cancer registry data. Results Overall, genotyping using SNP chips performed well compared with sequencing; sensitivity, specificity, positive predictive value, and negative predictive value were all above 99% for 108 574 common variants directly genotyped on the SNP chips and sequenced in the UK Biobank. However, the likelihood of a true positive result decreased dramatically with decreasing variant frequency; for variants that are very rare in the population, with a frequency below 0.001% in UK Biobank, the positive predictive value was very low and only 16% of 4757 heterozygous genotypes from the SNP chips were confirmed with sequencing data. Results were similar for SNP chip data from the Personal Genome Project, and 20/21 individuals analysed had at least one false positive rare pathogenic variant that had been incorrectly genotyped. For pathogenic variants in the BRCA1 and BRCA2 genes, which are individually very rare, the overall performance metrics for the SNP chips versus sequencing in the UK Biobank were: sensitivity 34.6%, specificity 98.3%, positive predictive value 4.2%, and negative predictive value 99.9%. Rates of BRCA related cancers in UK Biobank participants with a positive SNP chip result were similar to those for age matched controls (odds ratio 1.31, 95% confidence interval 0.99 to 1.71) because the vast majority of variants were false positives, whereas sequence positive participants had a significantly increased risk (odds ratio 4.05, 2.72 to 6.03). Conclusions SNP chips are extremely unreliable for genotyping very rare pathogenic variants and should not be used to guide health decisions without validation. more...
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- 2021
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7. Genome-wide association analyses of chronotype in 697,828 individuals provides insights into circadian rhythms
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Jones, SE, Lane, JM, Wood, AR, van Hees, VT, Tyrrell, J, Beaumont, RN, Jeffries, AR, Dashti, HS, Hillsdon, M, Ruth, KS, Tuke, MA, Yaghootkar, H, Sharp, SA, Jie, YJ, Thompson, WD, Harrison, JW, Dawes, A, Byrne, EM, Tiemeier, Henning, Allebrandt, KV, Bowden, J, Ray, DW, Freathy, RM, Murray, A, Mazzotti, DR, Gehrman, PR, Lawlor, DA, Frayling, TM, Rutter, MK, Hinds, DA, Saxena, R, Weedon, MN, Agee, M, Alipanahi, B, Auton, A, Bell, RK, Bryc, K, Elson, SL, Fontanillas, P, Furlotte, NA, Huber, KE, Kleinman, A, Litterman, NK, McCreight, JC, McIntyre, MH, Mountain, JL, Noblin, ES, Northover, CAM, Pitts, SJ, Sathirapongsasuti, JF, Sazonova, OV, Shelton, JF, Shringarpure, S, Tian, C, Tung, JY, Vacic, V, Wilson, CH, Epidemiology, and Psychiatry more...
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- 2019
8. Genetic studies of accelerometer-based sleep measures in 85,670 individuals yield new insights into human sleep behaviour
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Andrew R. Wood, Meena Kumari, Richa Saxena, Robin N Beaumont, Hassan S. Dashti, Najaf Amin, Michael N. Weedon, Hees VTv, Hanieh Yaghootkar, Martin K. Rutter, Jie Y, Timothy M. Frayling, Anna Murray, Desana Kocevska, Melvyn Hillsdon, Séverine Sabia, Z. Kutalik, Samuel E. Jones, Henning Tiemeier, Pedro Marques-Vidal, Diego R. Mazzotti, Ruth Ks, Marcus A. Tuke, der Spek Av, Annemarie I. Luik, Jacqueline M. Lane, Seth A. Sharp, Rachel M. Freathy, P Gehrman, Jess Tyrrell, Jorgen Engmann, and James W. Harrison more...
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0303 health sciences ,Genetic variants ,Disease ,Biology ,Accelerometer ,Sleep in non-human animals ,Biobank ,03 medical and health sciences ,0302 clinical medicine ,Sleep behaviour ,Accelerometer data ,030217 neurology & neurosurgery ,030304 developmental biology ,Clinical psychology - Abstract
Sleep is an essential human function but its regulation is poorly understood. Identifying genetic variants associated with quality, quantity and timing of sleep will provide biological insights into the regulation of sleep and potential links with disease. Using accelerometer data from 85,670 individuals in the UK Biobank, we performed a genome-wide association study of 8 accelerometer-derived sleep traits, 5 of which are not accessible through self-report alone. We identified 47 genetic associations across the sleep traits (P-8) and replicated our findings in 5,819 individuals from 3 independent studies. These included 26 novel associations for sleep quality and 10 for nocturnal sleep duration. The majority of newly identified variants were associated with a single sleep trait, except for variants previously associated with restless legs syndrome that were associated with multiple sleep traits. Of the new associated and replicated sleep duration loci, we were able to fine-map a missense variant (p.Tyr727Cys) in PDE11A, a dual-specificity 3’,5’-cyclic nucleotide phosphodiesterase expressed in the hippocampus, as the likely causal variant. As a group, sleep quality loci were enriched for serotonin processing genes and all sleep traits were enriched for cerebellar-expressed genes. These findings provide new biological insights into sleep characteristics. more...
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- 2018
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9. Genetic studies of accelerometer-based sleep measures yield new insights into human sleep behaviour
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Jones, S. (S.), van Hees, V.T., Mazzotti, D.R., Marques-Vidal, P. (Pedro), Sabia, S., Spek, A. (Ashley) van der, Dashti, HS, Engmann, J, Kocevska, D. (Desana), Tyrrell, A.W.R., Beaumont, RN, Hillsdon, M., Ruth, KS, Tuke, MA, Yaghootkar, H. (Hanieh), Sharp, S.A., Ji, Y.J., Harrison, J.W., Freathy, R.M. (Rachel), Murray, A. (Anna), Luik, A.I. (Annemarie), Amin, N. (Najaf), Lane, J.M., Saxena, R. (Richa), Rutter, M.K., Tiemeier, H.W. (Henning), Kutalik, Z. (Zoltán), Kumari, M. (Meena), Frayling, T.M. (Timothy), Weedo, M.N. (Michael), Gehrman, P.R. (Philip), Wood, A.R. (Andrew), Jones, S. (S.), van Hees, V.T., Mazzotti, D.R., Marques-Vidal, P. (Pedro), Sabia, S., Spek, A. (Ashley) van der, Dashti, HS, Engmann, J, Kocevska, D. (Desana), Tyrrell, A.W.R., Beaumont, RN, Hillsdon, M., Ruth, KS, Tuke, MA, Yaghootkar, H. (Hanieh), Sharp, S.A., Ji, Y.J., Harrison, J.W., Freathy, R.M. (Rachel), Murray, A. (Anna), Luik, A.I. (Annemarie), Amin, N. (Najaf), Lane, J.M., Saxena, R. (Richa), Rutter, M.K., Tiemeier, H.W. (Henning), Kutalik, Z. (Zoltán), Kumari, M. (Meena), Frayling, T.M. (Timothy), Weedo, M.N. (Michael), Gehrman, P.R. (Philip), and Wood, A.R. (Andrew) more...
- Abstract
Sleep is an essential human function but its regulation is poorly understood. Using accelerometer data from 85,670 UK Biobank participants, we perform a genome-wide association study of 8 derived sleep traits representing sleep quality, quantity and timing, and validate our findings in 5,819 individuals. We identify 47 genetic associations at P < 5 × 10−8, of which 20 reach a stricter threshold of P < 8 × 10−10. These include 26 novel associations with measures of sleep quality and 10 with nocturnal sleep duration. The majority of identified variants associate with a single sleep trait, except for variants previously associated with restless legs syndrome. For sleep duration we identify a missense variant (p.Tyr727Cys) in PDE11A as the likely causal variant. As a group, sleep quality loci are enriched for serotonin processing genes. Although accelerometer-derived measures of sleep are imperfect and may be affected by restless legs syndrome, these findings provide new biological insights into sleep compared to previous efforts based on self-report sleep measures. more...
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- 2019
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10. Genome-wide association analyses of chronotype in 697,828 individuals provides insights into circadian rhythms
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Jones, S. (S.), Lane, J.M., Wood, A.R. (Andrew), van Hees, V.T., Tyrrell, A.W.R., Beaumont, RN, Jeffries, A.R., Dashti, HS, Hillsdon, M., Ruth, KS, Tuke, MA, Yaghootkar, H. (Hanieh), Sharp, S.A., Jie, Y.J., Thompson, W.D., Harrison, J.W., Dawes, A., Byrne, E.M. (Enda), Tiemeier, H.W. (Henning), Allebrandt, K.V., Bowden, J., Ray, D.W., Freathy, R.M. (Rachel), Murray, A. (Anna), Mazzotti, D.R., Gehrman, P.R. (Philip), Lawlor, D.A. (Debbie), Frayling, T.M. (Timothy), Rutter, M.K., Hinds, DA, Saxena, R. (Richa), Weedo, M.N. (Michael), Agee, M., Alipanahi, B., Auton, A., Bell, R.K., Bryc, K., Elson, S.L., Fontanillas, P. (Pierre), Furlotte, NA, Huber, K.E., Kleinman, A, Litterman, N.K., McCreight, J.C., McIntyre, M.H., Mountain, J.L., Noblin, E.S., Northover, C.A.M., Pitts, S.J. (Steven), Sathirapongsasuti, JF, Sazonova, O.V., Shelton, J.F., Shringarpure, S., Tian, C, Tung, JY, Vacic, V., Wilson, C.H., Jones, S. (S.), Lane, J.M., Wood, A.R. (Andrew), van Hees, V.T., Tyrrell, A.W.R., Beaumont, RN, Jeffries, A.R., Dashti, HS, Hillsdon, M., Ruth, KS, Tuke, MA, Yaghootkar, H. (Hanieh), Sharp, S.A., Jie, Y.J., Thompson, W.D., Harrison, J.W., Dawes, A., Byrne, E.M. (Enda), Tiemeier, H.W. (Henning), Allebrandt, K.V., Bowden, J., Ray, D.W., Freathy, R.M. (Rachel), Murray, A. (Anna), Mazzotti, D.R., Gehrman, P.R. (Philip), Lawlor, D.A. (Debbie), Frayling, T.M. (Timothy), Rutter, M.K., Hinds, DA, Saxena, R. (Richa), Weedo, M.N. (Michael), Agee, M., Alipanahi, B., Auton, A., Bell, R.K., Bryc, K., Elson, S.L., Fontanillas, P. (Pierre), Furlotte, NA, Huber, K.E., Kleinman, A, Litterman, N.K., McCreight, J.C., McIntyre, M.H., Mountain, J.L., Noblin, E.S., Northover, C.A.M., Pitts, S.J. (Steven), Sathirapongsasuti, JF, Sazonova, O.V., Shelton, J.F., Shringarpure, S., Tian, C, Tung, JY, Vacic, V., and Wilson, C.H. more...
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- 2019
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11. Genetic studies of accelerometer-based sleep measures yield new insights into human sleep behaviour
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Jones, SE, van Hees, VT, Mazzotti, DR, Marques-Vidal, P, Sabia, S, van der Spek, Ashley, Dashti, HS, Engmann, J, Kocevska, Desi, Tyrrell, J, Beaumont, RN, Hillsdon, M, Ruth, KS, Tuke, MA, Yaghootkar, H, Sharp, SA, Ji, YJ, Harrison, JW, Freathy, RM, Murray, A, Luik, Annemarie, Amin, Najaf, Lane, JM, Saxena, R, Rutter, MK, Tiemeier, Henning, Kutalik, Z, Kumari, M, Frayling, TM, Weedon, MN, Gehrman, PR, Wood, AR, Jones, SE, van Hees, VT, Mazzotti, DR, Marques-Vidal, P, Sabia, S, van der Spek, Ashley, Dashti, HS, Engmann, J, Kocevska, Desi, Tyrrell, J, Beaumont, RN, Hillsdon, M, Ruth, KS, Tuke, MA, Yaghootkar, H, Sharp, SA, Ji, YJ, Harrison, JW, Freathy, RM, Murray, A, Luik, Annemarie, Amin, Najaf, Lane, JM, Saxena, R, Rutter, MK, Tiemeier, Henning, Kutalik, Z, Kumari, M, Frayling, TM, Weedon, MN, Gehrman, PR, and Wood, AR more...
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- 2019
12. Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity (vol 50, pg 26, 2018)
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Turcot, V, Lu, Y, Highland, HM, Schurmann, C, Justice, AE, Fine, RS, Bradfield, JP, Esko, T, Giri, A, Graff, M, Guo, X, Hendricks, AE, Karaderi, T, Lempradl, A, Locke, AE, Mahajan, A, Marouli, E, Sivapalaratnam, S, Young, KL, Alfred, T, Feitosa, MF, Masca, NGD, Manning, AK, Medina-Gomez, C, Mudgal, P, Ng, MCY, Reiner, AP, Vedantam, S, Willems, SM, Winkler, TW, Abecasis, G, Aben, KK, Alam, DS, Alharthi, SE, Allison, M, Amouyel, P, Asselbergs, FW, Auer, PL, Balkau, B, Bang, LE, Barroso, I, Bastarache, L, Benn, M, Bergmann, S, Bielak, LF, Bluher, M, Boehnke, M, Boeing, H, Boerwinkle, E, Boger, CA, Bork-Jensen, J, Bots, ML, Bottinger, EP, Bowden, DW, Brandslund, I, Breen, G, Brilliant, MH, Broer, L, Brumat, M, Burt, AA, Butterworth, AS, Campbell, PT, Cappellani, S, Carey, DJ, Catamo, E, Caulfield, MJ, Chambers, JC, Chasman, DI, Chen, Y-DI, Chowdhury, R, Christensen, C, Chu, AY, Cocca, M, Collins, FS, Cook, JP, Corley, J, Galbany, JC, Cox, AJ, Crosslin, DS, Cuellar-Partida, G, D'Eustacchio, A, Danesh, J, Davies, G, Bakker, PIW, Groot, MCH, Mutsert, R, Deary, IJ, Dedoussis, G, Demerath, EW, Heijer, M, Hollander, AI, Ruijter, HM, Dennis, JG, Denny, JC, Di Angelantonio, E, Drenos, F, Du, M, Dube, M-P, Dunning, AM, Easton, DF, Edwards, TL, Ellinghaus, D, Ellinor, PT, Elliott, P, Evangelou, E, Farmaki, A-E, Farooqi, IS, Faul, JD, Fauser, S, Feng, S, Ferrannini, E, Ferrieres, J, Florez, JC, Ford, I, Fornage, M, Franco, OH, Franke, A, Franks, PW, Friedrich, N, Frikke-Schmidt, R, Galesloot, TE, Gan, W, Gandin, I, Gasparini, P, Gibson, J, Giedraitis, V, Gjesing, AP, Gordon-Larsen, P, Gorski, M, Grabe, H-J, Grant, SFA, Grarup, N, Griffiths, HL, Grove, ML, Gudnason, V, Gustafsson, S, Haessler, J, Hakonarson, H, Hammerschlag, AR, Hansen, T, Harris, KM, Harris, TB, Hattersley, AT, Have, CT, Hayward, C, He, L, Heard-Costa, NL, Heath, AC, Heid, IM, Helgeland, O, Hernesniemi, J, Hewitt, AW, Holmen, OL, Hovingh, GK, Howson, JMM, Hu, Y, Huang, PL, Huffman, JE, Ikram, MA, Ingelsson, E, Jackson, AU, Jansson, J-H, Jarvik, GP, Jensen, GB, Jia, Y, Johansson, S, Jorgensen, ME, Jorgensen, T, Jukema, JW, Kahali, B, Kahn, RS, Kahonen, M, Kamstrup, PR, Kanoni, S, Kaprio, J, Karaleftheri, M, Kardia, SLR, Karpe, F, Kathiresan, S, Kee, F, Kiemeney, LA, Kim, E, Kitajima, H, Komulainen, P, Kooner, JS, Kooperberg, C, Korhonen, T, Kovacs, P, Kuivaniemi, H, Kutalik, Z, Kuulasmaa, K, Kuusisto, J, Laakso, M, Lakka, TA, Lamparter, D, Lange, EM, Lange, LA, Langenberg, C, Larson, EB, Lee, NR, Lehtimaki, T, Lewis, CE, Li, H, Li, J, Li-Gao, R, Lin, H, Lin, K-H, Lin, L-A, Lin, X, Lind, L, Lindstrom, J, Linneberg, A, Liu, C-T, Liu, DJ, Liu, Y, Lo, KS, Lophatananon, A, Lotery, AJ, Loukola, A, Luan, J, Lubitz, SA, Lyytikainen, L-P, Mannisto, S, Marenne, G, Mazul, AL, McCarthy, MI, McKean-Cowdin, R, Medland, SE, Meidtner, K, Milani, L, Mistry, V, Mitchell, P, Mohlke, KL, Moilanen, L, Moitry, M, Montgomery, GW, Mook-Kanamori, DO, Moore, C, Mori, TA, Morris, AD, Morris, AP, Mueller-Nurasyid, M, Munroe, PB, Nalls, MA, Narisu, N, Nelson, CP, Neville, M, Nielsen, SF, Nikus, K, Njolstad, PR, Nordestgaard, BG, Nyholt, DR, O'Connel, JR, O'Donoghue, ML, Loohuis, LMO, Ophoff, RA, Owen, KR, Packard, CJ, Padmanabhan, S, Palmer, CNA, Palmer, ND, Pasterkamp, G, Patel, AP, Pattie, A, Pedersen, O, Peissig, PL, Peloso, GM, Pennell, CE, Perola, M, Perry, JA, Perry, JRB, Pers, TH, Person, TN, Peters, A, Petersen, ERB, Peyser, PA, Pirie, A, Polasek, O, Polderman, TJ, Puolijoki, H, Raitakari, OT, Rasheed, A, Rauramaa, R, Reilly, DF, Renstrom, F, Rheinberger, M, Ridker, PM, Rioux, JD, Rivas, MA, Roberts, DJ, Robertson, NR, Robino, A, Rolandsson, O, Rudan, I, Ruth, KS, Saleheen, D, Salomaa, V, Samani, NJ, Sapkota, Y, Sattar, N, Schoen, RE, Schreiner, PJ, Schulze, MB, Scott, RA, Segura-Lepe, MP, Shah, SH, Sheu, WH-H, Sim, X, Slater, AJ, Small, KS, Smith, AV, Southam, L, Spector, TD, Speliotes, EK, Starr, JM, Stefansson, K, Steinthorsdottir, V, Stirrups, KE, Strauch, K, Stringham, HM, Stumvoll, M, Sun, L, Surendran, P, Swift, AJ, Tada, H, Tansey, KE, Tardif, J-C, Taylor, KD, Teumer, A, Thompson, DJ, Thorleifsson, G, Thorsteinsdottir, U, Thuesen, BH, Tonjes, A, Tromp, G, Trompet, S, Tsafantakis, E, Tuomilehto, J, Tybjaerg-Hansen, A, Tyrer, JP, Uher, R, Uitterlinden, AG, Uusitupa, M, Laan, SW, Duijn, CM, Leeuwen, N, van Setten, J, Vanhala, M, Varbo, A, Varga, TV, Varma, R, Edwards, DRV, Vermeulen, SH, Veronesi, G, Vestergaard, H, Vitart, V, Vogt, TF, Volker, U, Vuckovic, D, Wagenknecht, LE, Walker, M, Wallentin, L, Wang, F, Wang, CA, Wang, S, Wang, Y, Ware, EB, Wareham, NJ, Warren, HR, Waterworth, DM, Wessel, J, White, HD, Willer, CJ, Wilson, JG, Witte, DR, Wood, AR, Wu, Y, Yaghootkar, H, Yao, J, Yao, P, Yerges-Armstrong, LM, Young, R, Zeggini, E, Zhan, X, Zhang, W, Zhao, JH, Zhao, W, Zhou, W, Zondervan, KT, Consortium, GG, Rotter, JI, Pospisilik, JA, Rivadeneira, F, Borecki, IB, Deloukas, P, Frayling, TM, Lettre, G, North, KE, Lindgren, CM, Hirschhorn, JN, Loos, RJF, Vascular Medicine, ACS - Atherosclerosis & ischemic syndromes, and Amsterdam Cardiovascular Sciences more...
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- 2018
13. Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity (vol 50, pg 765, 2017)
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Turcot, V, Lu, Y, Highland, HM, Schurmann, C, Justice, AE, Fine, RS, Bradfield, JP, Esko, T, Giri, A, Graff, M, Guo, X, Hendricks, AE, Karaderi, T, Lempradl, A, Locke, AE, Mahajan, A, Marouli, E, Sivapalaratnam, S, Young, KL, Alfred, T, Feitosa, MF, Masca, NGD, Manning, AK, Medina-Gomez, C, Mudgal, P, Ng, MCY, Reiner, AP, Vedantam, S, Willems, SM, Winkler, TW, Abecasis, G, Aben, KK, Alam, DS, Alharthi, SE, Allison, M, Amouyel, P, Asselbergs, FW, Auer, PL, Balkau, B, Bang, LE, Barroso, I, Bastarache, L, Benn, M, Bergmann, S, Bielak, LF, Bluher, M, Boehnke, M, Boeing, H, Boerwinkle, E, Boger, CA, Bork-Jensen, J, Bots, ML, Bottinger, EP, Bowden, DW, Brandslund, I, Breen, G, Brilliant, MH, Broer, L, Brumat, M, Burt, AA, Butterworth, AS, Campbell, PT, Cappellani, S, Carey, DJ, Catamo, E, Caulfield, MJ, Chambers, JC, Chasman, DI, Chen, Y-DI, Chowdhury, R, Christensen, C, Chu, AY, Cocca, M, Collins, FS, Cook, JP, Corley, J, Galbany, JC, Cox, AJ, Crosslin, DS, Cuellar-Partida, G, D'Eustacchio, A, Danesh, J, Davies, G, Bakker, PIW, Groot, MCH, Mutsert, R, Deary, IJ, Dedoussis, G, Demerath, EW, Heijer, M, Hollander, AI, Ruijter, HM, Dennis, JG, Denny, JC, Angelantonio, E, Drenos, F, Du, M, Dube, M-P, Dunning, AM, Easton, DF, Edwards, TL, Ellinghaus, D, Ellinor, PT, Elliott, P, Evangelou, E, Farmaki, A-E, Farooqi, IS, Faul, JD, Fauser, S, Feng, S, Ferrannini, E, Ferrieres, J, Florez, JC, Ford, I, Fornage, M, Franco, OH, Franke, A, Franks, PW, Friedrich, N, Frikke-Schmidt, R, Galesloot, TE, Gan, W, Gandin, I, Gasparini, P, Gibson, J, Giedraitis, V, Gjesing, AP, Gordon-Larsen, P, Gorski, M, Grabe, H-J, Grant, SFA, Grarup, N, Griffiths, HL, Grove, ML, Gudnason, V, Gustafsson, S, Haessler, J, Hakonarson, H, Hammerschlag, AR, Hansen, T, Harris, KM, Harris, TB, Hattersley, AT, Have, CT, Hayward, C, He, L, Heard-Costa, NL, Heath, AC, Heid, IM, Helgeland, O, Hernesniemi, J, Hewitt, AW, Holmen, OL, Hovingh, GK, Howson, JMM, Hu, Y, Huang, PL, Huffman, JE, Ikram, MA, Ingelsson, E, Jackson, AU, Jansson, J-H, Jarvik, GP, Jensen, GB, Jia, Y, Johansson, S, Jorgensen, ME, Jorgensen, T, Jukema, JW, Kahali, B, Kahn, RS, Kahonen, M, Kamstrup, PR, Kanoni, S, Kaprio, J, Karaleftheri, M, Kardia, SLR, Karpe, F, Kathiresan, S, Kee, F, Kiemeney, LA, Kim, E, Kitajima, H, Komulainen, P, Kooner, JS, Kooperberg, C, Korhonen, T, Kovacs, P, Kuivaniemi, H, Kutalik, Z, Kuulasmaa, K, Kuusisto, J, Laakso, M, Lakka, TA, Lamparter, D, Lange, EM, Lange, LA, Langenberg, C, Larson, EB, Lee, NR, Lehtimaki, T, Lewis, CE, Li, H, Li, J, Li-Gao, R, Lin, H, Lin, K-H, Lin, L-A, Lin, X, Lind, L, Lindstrom, J, Linneberg, A, Liu, C-T, Liu, DJ, Liu, Y, Lo, KS, Lophatananon, A, Lotery, AJ, Loukola, A, Luan, J, Lubitz, SA, Lyytikainen, L-P, Mannisto, S, Marenne, G, Mazul, AL, McCarthy, MI, McKean-Cowdin, R, Medland, SE, Meidtner, K, Milani, L, Mistry, V, Mitchell, P, Mohlke, KL, Moilanen, L, Moitry, M, Montgomery, GW, Mook-Kanamori, DO, Moore, C, Mori, TA, Morris, AD, Morris, AP, Mueller-Nurasyid, M, Munroe, PB, Nalls, MA, Narisu, N, Nelson, CP, Neville, M, Nielsen, SF, Nikus, K, Njolstad, PR, Nordestgaard, BG, Nyholt, DR, O'Connel, JR, O'Donoghue, ML, Loohuis, LMO, Ophoff, RA, Owen, KR, Packard, CJ, Padmanabhan, S, Palmer, CNA, Palmer, ND, Pasterkamp, G, Patel, AP, Pattie, A, Pedersen, O, Peissig, PL, Peloso, GM, Pennell, CE, Perola, M, Perry, JA, Perry, JRB, Pers, TH, Person, TN, Peters, A, Petersen, ERB, Peyser, PA, Pirie, A, Polasek, O, Polderman, TJ, Puolijoki, H, Raitakari, OT, Rasheed, A, Rauramaa, R, Reilly, DF, Renstrom, F, Rheinberger, M, Ridker, PM, Rioux, JD, Rivas, MA, Roberts, DJ, Robertson, NR, Robino, A, Rolandsson, O, Rudan, I, Ruth, KS, Saleheen, D, Salomaa, V, Samani, NJ, Sapkota, Y, Sattar, N, Schoen, RE, Schreiner, PJ, Schulze, MB, Scott, RA, Segura-Lepe, MP, Shah, SH, Sheu, WH-H, Sim, X, Slater, AJ, Small, KS, Smith, AV, Southam, L, Spector, TD, Speliotes, EK, Starr, JM, Stefansson, K, Steinthorsdottir, V, Stirrups, KE, Strauch, K, Stringham, HM, Stumvoll, M, Sun, L, Surendran, P, Swift, AJ, Tada, H, Tansey, KE, Tardif, J-C, Taylor, KD, Teumer, A, Thompson, DJ, Thorleifsson, G, Thorsteinsdottir, U, Thuesen, BH, Tonjes, A, Tromp, G, Trompet, S, Tsafantakis, E, Tuomilehto, J, Tybjaerg-Hansen, A, Tyrer, JP, Uher, R, Uitterlinden, AG, Uusitupa, M, Laan, SW, Duijn, CM, Leeuwen, N, van Setten, J, Vanhala, M, Varbo, A, Varga, TV, Varma, R, Edwards, DRV, Vermeulen, SH, Veronesi, G, Vestergaard, H, Vitart, V, Vogt, TF, Volker, U, Vuckovic, D, Wagenknecht, LE, Walker, M, Wallentin, L, Wang, F, Wang, CA, Wang, S, Wang, Y, Ware, EB, Wareham, NJ, Warren, HR, Waterworth, DM, Wessel, J, White, HD, Willer, CJ, Wilson, JG, Witte, DR, Wood, AR, Wu, Y, Yaghootkar, H, Yao, J, Yao, P, Yerges-Armstrong, LM, Young, R, Zeggini, E, Zhan, X, Zhang, W, Zhao, JH, Zhao, W, Zhou, W, Zondervan, KT, Rotter, JI, Pospisilik, JA, Rivadeneira, F, Borecki, IB, Deloukas, P, Frayling, TM, Lettre, G, North, KE, Lindgren, CM, Hirschhorn, JN, Loos, RJF, Graduate School, Vascular Medicine, ACS - Atherosclerosis & ischemic syndromes, and Amsterdam Cardiovascular Sciences more...
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- 2018
14. A common allele in FGF21 associated with preference for sugar consumption lowers body fat in the lower body and increases blood pressure
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Jonathan M. Locke, William D. Thompson, Jess Tyrrell, Rachel M. Freathy, West B, Beaumont Rn, James W. Harrison, Niels Grarup, C M Lindgren, Anna Murray, Francesco Casanova, Andrew R. Wood, Ruth Ks, Seth A. Sharp, Timothy M. Frayling, Yingjie Ji, Marcus A. Tuke, Samuel E. Jones, Michael N. Weedon, and Hanieh Yaghootkar more...
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2. Zero hunger ,Genetics ,0303 health sciences ,medicine.medical_specialty ,FGF21 ,030209 endocrinology & metabolism ,Biology ,Phenotype ,03 medical and health sciences ,0302 clinical medicine ,Lower body ,Blood pressure ,Endocrinology ,Weight loss ,Internal medicine ,medicine ,Allele ,medicine.symptom ,Gene ,030304 developmental biology ,Hormone - Abstract
SummaryFibroblast Growth Factor 21 (FGF21) is a hormone that induces weight loss in model organisms. These findings have led to trials in humans of FGF21 analogues with some showing weight loss and lipid lowering effects. Recent genetic studies have shown that a common allele in the FGF21 gene alters the balance of macronutrients consumed but there was little evidence of an effect on metabolic traits. We studied a common FGF21 allele (A:rs838133) in 451,099 people from the UK Biobank study. We replicated the association between the A allele and higher percentage carbohydrate intake. We then showed that this allele is more strongly associated with body fat distribution, with less fat in the lower body, and higher blood pressure, than it is with BMI, where there is only nominal evidence of an effect. These human phenotypes of naturally occurring variation in the FGF21 gene will inform decisions about FGF21’s therapeutic potential. more...
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- 2017
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15. Mosaic Turner syndrome shows reduced phenotypic penetrance in an adult population study compared to clinically ascertained cases
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Jess Tyrrell, Andrew R. Wood, Claire L. S. Turner, Mollie E. Donohoe, Anna Murray, Samuel E. Jones, Marcus A. Tuke, Antonia Brooke, Michael N. Weedon, Ruth Ks, Beaumont Rn, Morag N Collinson, Hanieh Yaghootkar, Timothy M. Frayling, and Rachel M. Freathy more...
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Gynecology ,0303 health sciences ,medicine.medical_specialty ,business.industry ,030305 genetics & heredity ,Aneuploidy ,030209 endocrinology & metabolism ,Triple X syndrome ,medicine.disease ,Penetrance ,3. Good health ,Birth rate ,03 medical and health sciences ,0302 clinical medicine ,Turner syndrome ,Menarche ,medicine ,business ,X chromosome ,SNP array - Abstract
Women with X chromosome aneuploidy such as 45,X (Turner syndrome) or 47,XXX (Triple X syndrome) present with characteristics including differences in stature, increased cardiovascular disease risk and primary ovarian insufficiency. Many women with X chromosome aneuploidy undergo lifetime clinical monitoring for possible complications. However, ascertainment of cases in the clinic may mean that the phenotypic penetrance is overestimated. Studies of prenatally ascertained X chromosome aneuploidy cases have limited follow-up data and so the long-term consequences into adulthood are often not reported. We aimed to characterise the prevalence and phenotypic consequences of X chromosome aneuploidy in a large population of women over 40 years of age. We detected 30 women with 45,X, 186 with mosaic 45,X/46,XX and 110 with 47,XXX among 244,848 UK Biobank women, using SNP array data. The prevalence of non-mosaic 45,X (1/8,162) and 47,XXX (1/2,226) was lower than expected, but was higher for mosaic 45,X/46,XX (1/1,316). The characteristics of women with 45,X were consistent with the characteristics of a clinically recognised Turner syndrome phenotype, including a 17.2cm shorter stature (SD = 5.72cm; P = 1.5 × 10−53) and 16/30 did not report an age at menarche. The phenotype of women with 47,XXX included taller stature (5.3cm; SD = 5.52cm; P = 5.8 × 10−20), earlier menopause age (5.12 years; SD = 5.1 years; P = 1.2 x 10−14) and a lower fluid intelligence score (24%; SD = 29.7%; P = 3.7 × 10−8). In contrast, the characteristics of women with mosaic 45,X/46,XX were much less pronounced than expected. Women with mosaic 45,X/46,XX were less short, had a normal reproductive lifespan and birth rate, and no reported cardiovascular complications. In conclusion, the availability of data from 244,848 women allowed us to assess the phenotypic penetrance of traits associated with X chromosome aneuploidy in an adult population setting. Our results suggest that the clinical management of women with 45,X/46,XX mosaicism should be minimal, particularly those identified incidentally.FundingNone more...
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- 2017
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16. Genome-wide association study of offspring birth weight in 86 577 women identifies five novel loci and highlights maternal genetic effects that are independent of fetal genetics
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Beaumont, RN, Warrington, NM, Cavadino, A, Tyrrell, J, Nodzenski, M, Horikoshi, M, Geller, F, Myhre, R, Richmond, Rebecca, Paternoster, L, Bradfield, JP, Kreiner-Moller, E, Huikari, V, Metrustry, S, Lunetta, KL, Painter, JN, Hottenga, JJ, Allard, C, Barton, SJ, Espinosa, A, Marsh, JA, Potter, C, Zhang, G, Ang, W, Berry, DJ, Bouchard, L, Das, S, Hakonarson, H, Heikkinen, J, Helgeland, O, Hocher, B, Hofman, Bert, Inskip, HM, Jones, SE, Kogevinas, M, Lind, PA, Marullo, L, Medland, SE, Murray, A, Murray, JC, Njolstad, PR, Nohr, EA, Reichetzeder, C, Ring, SM, Ruth, KS, Santa-Marina, L, Scholtens, DM, Sebert, S, Sengpiel, V, Tuke, MA, Vaudel, M, Weedon, MN, Willemsen, G, Wood, AR, Yaghootkar, H, Muglia, LJ, Bartels, M, Relton, CL, Pennell, CE, Chatzi, L, Estivill, X, Holloway, JW, Boomsma, DI, Montgomery, GW, Murabito, JM, Spector, TD, Power, C, Jarvelin, MR, Bisgaard, H, Grant, SFA, Sorensen, TIA, Jaddoe, Vincent, Jacobsson, B, Melbye, M, McCarthy, MI, Hattersley, AT, Hayes, MG, Frayling, TM, Hivert, MF, Felix, Janine, Hypponen, E, Lowe, WL, Evans, DM, Lawlor, DA, Feenstra, B, Freathy, RM, Beaumont, RN, Warrington, NM, Cavadino, A, Tyrrell, J, Nodzenski, M, Horikoshi, M, Geller, F, Myhre, R, Richmond, Rebecca, Paternoster, L, Bradfield, JP, Kreiner-Moller, E, Huikari, V, Metrustry, S, Lunetta, KL, Painter, JN, Hottenga, JJ, Allard, C, Barton, SJ, Espinosa, A, Marsh, JA, Potter, C, Zhang, G, Ang, W, Berry, DJ, Bouchard, L, Das, S, Hakonarson, H, Heikkinen, J, Helgeland, O, Hocher, B, Hofman, Bert, Inskip, HM, Jones, SE, Kogevinas, M, Lind, PA, Marullo, L, Medland, SE, Murray, A, Murray, JC, Njolstad, PR, Nohr, EA, Reichetzeder, C, Ring, SM, Ruth, KS, Santa-Marina, L, Scholtens, DM, Sebert, S, Sengpiel, V, Tuke, MA, Vaudel, M, Weedon, MN, Willemsen, G, Wood, AR, Yaghootkar, H, Muglia, LJ, Bartels, M, Relton, CL, Pennell, CE, Chatzi, L, Estivill, X, Holloway, JW, Boomsma, DI, Montgomery, GW, Murabito, JM, Spector, TD, Power, C, Jarvelin, MR, Bisgaard, H, Grant, SFA, Sorensen, TIA, Jaddoe, Vincent, Jacobsson, B, Melbye, M, McCarthy, MI, Hattersley, AT, Hayes, MG, Frayling, TM, Hivert, MF, Felix, Janine, Hypponen, E, Lowe, WL, Evans, DM, Lawlor, DA, Feenstra, B, and Freathy, RM more...
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- 2018
17. Large-scale GWAS identifies multiple loci for hand grip strength providing biological insights into muscular fitness
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Willems, SM, Wright, DJ, Day, FR, Trajanoska, K, Joshi, PK, Morris, JA, Matteini, AM, Garton, FC, Grarup, N, Oskolkov, N, Thalamuthu, A, Mangino, M, Liu, J, Demirkan, A, Lek, M, Xu, L, Wang, G, Oldmeadow, C, Gaulton, KJ, Lotta, LA, Miyamoto-Mikami, E, Rivas, MA, White, T, Loh, P-R, Aadahl, M, Amin, N, Attia, JR, Austin, K, Benyamin, B, Brage, S, Cheng, Y-C, Cięszczyk, P, Derave, W, Eriksson, K-F, Eynon, N, Linneberg, A, Lucia, A, Massidda, M, Mitchell, BD, Miyachi, M, Murakami, H, Padmanabhan, S, Pandey, A, Papadimitriou, I, Rajpal, DK, Sale, C, Schnurr, TM, Sessa, F, Shrine, N, Tobin, MD, Varley, I, Wain, LV, Wray, NR, Lindgren, CM, MacArthur, DG, Waterworth, DM, McCarthy, MI, Pedersen, O, Khaw, K-T, Kiel, DP, Oei, L, Zheng, H-F, Forgetta, V, Leong, A, Ahmad, OS, Laurin, C, Mokry, LE, Ross, S, Elks, CE, Bowden, J, Warrington, NM, Murray, A, Ruth, KS, Tsilidis, KK, Medina-Gómez, C, Estrada, K, Bis, JC, Chasman, DI, Demissie, S, Enneman, AW, Hsu, Y-H, Ingvarsson, T, Kähönen, M, Kammerer, C, Lacroix, AZ, Li, G, Liu, C-T, Liu, Y, Lorentzon, M, Mägi, R, Mihailov, E, Milani, L, Moayyeri, A, Nielson, CM, Sham, PC, Siggeirsdotir, K, Sigurdsson, G, Stefansson, K, Trompet, S, Thorleifsson, G, Vandenput, L, van der Velde, N, Viikari, J, Xiao, S-M, Zhao, JH, Evans, DS, Cummings, SR, Cauley, J, Duncan, EL, de Groot, LCPGM, Esko, T, Gudnason, V, Harris, TB, Jackson, RD, Jukema, JW, Ikram, AMA, Karasik, D, Kaptoge, S, Kung, AWC, Lehtimäki, T, Lyytikäinen, L-P, Lips, P, Luben, R, Metspalu, A, van Meurs, JBJ, Minster, RL, Orwoll, E, Oei, E, Psaty, BM, Raitakari, OT, Ralston, SW, Ridker, PM, Robbins, JA, Smith, AV, Styrkarsdottir, U, Tranah, GJ, Thorstensdottir, U, Uitterlinden, AG, Zmuda, J, Zillikens, MC, Ntzani, EE, Evangelou, E, Ioannidis, JPA, Evans, DM, Ohlsson, C, Pitsiladis, Y, Fuku, N, Franks, PW, North, KN, van Duijn, CM, Mather, KA, Hansen, T, Hansson, O, Spector, T, Murabito, JM, Richards, JB, Rivadeneira, F, Langenberg, C, Perry, JRB, Wareham, NJ, Scott, RA, Willems, Sara M, Wright, Daniel J, Day, Felix R, Trajanoska, Katerina, Benyamin, Beben, Scott, Robert A, GEFOS Anytype Fracture Consortium, Wright, Daniel [0000-0003-3983-2093], Day, Felix [0000-0003-3789-7651], White, Thomas [0000-0001-8456-0803], Brage, Soren [0000-0002-1265-7355], Khaw, Kay-Tee [0000-0002-8802-2903], Langenberg, Claudia [0000-0002-5017-7344], Perry, John [0000-0001-6483-3771], Wareham, Nicholas [0000-0003-1422-2993], Apollo - University of Cambridge Repository, Epidemiology, and Internal Medicine more...
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Male ,Genome-wide association study ,VARIANTS ,Physical strength ,DISEASE ,Grip strength ,0302 clinical medicine ,Neoplasm Proteins/genetics ,GENETIC INFLUENCES ,European Continental Ancestry Group/genetics ,Aetiology ,education.field_of_study ,Hand Strength ,Deporte ,3. Good health ,Neoplasm Proteins ,muscular fitness ,Science & Technology - Other Topics ,Medical genetics ,medicine.medical_specialty ,Science ,1.1 Normal biological development and functioning ,European Continental Ancestry Group ,ta3111 ,Article ,White People ,General Biochemistry, Genetics and Molecular Biology ,03 medical and health sciences ,FRACTURES ,Genetics ,Humans ,GENOME-WIDE ASSOCIATION ,Genetik ,Polymorphism ,education ,METAANALYSIS ,Aged ,VLAG ,Global Nutrition ,Wereldvoeding ,Science & Technology ,ta1184 ,Prevention ,Hand/physiology ,Biology and Life Sciences ,INSTRUMENTS ,Hand ,GEFOS Any-Type of Fracture Consortium ,Nuclear Proteins/genetics ,Genetics, Population ,030104 developmental biology ,Genetic Loci ,030217 neurology & neurosurgery ,0301 basic medicine ,Transforming Growth Factor alpha/genetics ,General Physics and Astronomy ,Bioinformatics ,GROWTH-FACTOR-ALPHA ,Cohort Studies ,Medicine and Health Sciences ,2.1 Biological and endogenous factors ,ta315 ,Multidisciplinary ,Nuclear Proteins ,Single Nucleotide ,Middle Aged ,Multidisciplinary Sciences ,MENDELIAN RANDOMIZATION ,SKELETAL-MUSCLE ,Female ,Medical Genetics ,Adult ,Population ,Quantitative trait locus ,Biology ,Polymorphism, Single Nucleotide ,Underpinning research ,Hand strength ,MD Multidisciplinary ,Mendelian randomization ,medicine ,Life Science ,Membrane Proteins/genetics ,Deportes ,Medicinsk genetik ,Repressor Proteins/genetics ,Whites ,Actins/genetics ,Membrane Proteins ,General Chemistry ,Transforming Growth Factor alpha ,Genética ,Actins ,United Kingdom ,Repressor Proteins ,Good Health and Well Being ,Exercise Physiology and nutrition ,Musculoskeletal ,genome-wide association ,Genome-Wide Association Study - Abstract
Hand grip strength is a widely used proxy of muscular fitness, a marker of frailty, and predictor of a range of morbidities and all-cause mortality. To investigate the genetic determinants of variation in grip strength, we perform a large-scale genetic discovery analysis in a combined sample of 195,180 individuals and identify 16 loci associated with grip strength (P, Hand grip strength as a proxy of muscular fitness is a clinical predictor of mortality and morbidity. In a large-scale GWA study, the authors find 16 robustly associated genetic loci that highlight roles in muscle fibre structure and function, neuronal maintenance and nervous system signal transduction. more...
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- 2017
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18. Genomic analyses for age at menarche identify 389 independent signals and indicate BMI-independent effects of puberty timing on cancer susceptibility
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Nora Franceschini, Rico Rueedi, Gerardo Heiss, Behrooz Z. Alizadeh, Marike Gabrielson, Henry Völzke, Daniela Ruggiero, Judith S. Brand, Stig E. Bojesen, Iffat Rahman, Fergus J. Couch, Patrick Sulem, Harold Snieder, Jenny Chang-Claude, Caterina Barbieri, Ute Hamann, Hinds D, Pascal Guénel, Amanda B. Spurdle, Paul M. Ridker, Ulla Sovio, Roger L. Milne, Hamdi Mbarek, H Brenner, Hilary K. Finucane, Maristella Steri, Lude Franke, Emmi Tikkanen, Ivana Kolcic, Vitart, Ken K. Ong, Alison M. Dunning, Aarno Palotie, Caroline Hayward, Jouke J. Hottenga, Abhishek Sarkar, Stefania Lenarduzzi, Nicholas G. Martin, Katharina E. Schraut, Eva Albrecht, Hiltrud Brauch, Lisette Stolk, Joop S.E. Laven, Penelope A. Lind, Ilaria Gandin, Patrik K. E. Magnusson, Ellen A. Nohr, Tanguy Corre, Jing Hua Zhao, N J Timpson, Jenny A. Visser, Harald Grallert, P. A. Fasching, Susan M. Ring, Stöckl D, Grant W. Montgomery, Marzyeh Amini, Velez Edwards Dr, Thomas Meitinger, Qinghua Wang, David Karasik, Daniel I. Chasman, Nicholas J. Wareham, Alexander Teumer, Mellissa C. Southey, Kathryn L. Lunetta, S. E. Medland, Dieter Flesch-Janys, Maartje J. Hooning, Lili Milani, D Lambrechts, Ozren Polasek, Po-Ru Loh, James F. Wilson, Campbell A, Julian Peto, Ellen W. Demerath, Christian Gieger, de Geus Ej, Cox A, Javier Benítez, Mitul Shah, Eric Boerwinkle, Matthias W. Beckmann, Thorsteindottir U, Julie E. Buring, De Vivo I, Hannes Helgason, Paolo Radice, Tracy A. O'Mara, L. J. Launer, D. F. Gudbjartsson, Frits R. Rosendaal, C.A. Hartman, Stefania Bandinelli, Felix R. Day, Lynda M. Rose, van Dijk Kw, Natalia Perjakova, Anneli Pouta, Igor Rudan, Sven Bergmann, Kamila Czene, Georgia Chenevix-Trench, Pau Navarro, Sean Whalen, Heli Nevanlinna, Teresa Nutile, Diana L. Cousminer, Albert V. Smith, Massimo Mangino, Uwe Völker, Michela Traglia, Lindsay Fernández-Rhodes, Ayush Giri, Linda Broer, Albertine J. Oldehinkel, Isabel dos-Santos-Silva, Peter Vollenweider, Jian'an Luan, Nancy L. Pedersen, Irene L. Andrulis, Reedik Mägi, Robert Winqvist, Gonneke Willemsen, John L. Hopper, Gudnason, Marjanka K. Schmidt, David G. Hunter, Robert A. Scott, T.B. Harris, Joanne M. Murabito, David J. Porteous, Harry Campbell, Eleonora Porcu, D.I. Boomsma, Thibaud Boutin, M. A. Ikram, Doug Easton, Magdalena Zoledziewska, Meir J. Stampfer, Katherine S. Pollard, Eulalia Catamo, Tõnu Esko, M-R Jarvelin, Laura Crisponi, Claudia Langenberg, Marek Zygmunt, Antonietta Robino, Emily Hallberg, Manjeet K. Bolla, Ruth Ks, Bruce H W Wolffenbuttel, Lavinia Paternoster, Tyrer Jp, P. Kraft, George Davey-Smith, Robert Karlsson, Graham G. Giles, Jingmei Li, Pharoah Pd, Segrè Av, Marina Ciullo, Perry, Brumat Marco, Peter K. Joshi, Chunyan He, Sara Lindström, Joe Dennis, Thérèse Truong, Yongmei Liu, Anna Marie Mulligan, Mike A. Nalls, Cinzia Sala, K. Stefansson, Murray A, Debbie A Lawlor, Tung Jy, Deborah J. Thompson, Dennis O. Mook-Kanamori, Daniela Toniolo, Luigi Ferrucci, Peter Devilee, S. Chanock, Cristina Menni, George McMahon, Murielle Bochud, A. Metspalu, Tomohiro Tanaka, E. Widen, Hae Kyung Im, Dale R. Nyholt, Ilja M. Nolte, Thomas Brüning, Christina Meisinger, Annette Peters, Kyriaki Michailidou, Per Hall, Rossella Sorice, Genevieve Lachance, Johan G. Eriksson, Francesco Cucca, A.G. Uitterlinden, Z. Kutalik, Mark I. McCarthy, Frank B. Hu, Konstantin Strauch, Tim D. Spector, Elisabeth Altmaier, S. Ulivi, Alkes L. Price, Arto Mannermaa, Raymond Noordam, and de Mutsert R more...
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Genetics ,0303 health sciences ,03 medical and health sciences ,0302 clinical medicine ,030220 oncology & carcinogenesis ,Genotype ,Menarche ,Trait ,Cancer susceptibility ,Genomics ,Biology ,030304 developmental biology - Abstract
The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Here, we analyse 1000-Genome reference panel imputed genotype data on up to ~370,000 women and identify 389 independent signals (all P−8) for age at menarche, a notable milestone in female pubertal development. In Icelandic data from deCODE, these signals explain ~7.4% of the population variance in age at menarche, corresponding to one quarter of the estimated heritability. We implicate over 250 genes via coding variation or associated gene expression, and demonstrate enrichment across genes active in neural tissues. We identify multiple rare variants near the imprinted genes MKRN3 and DLK1 that exhibit large effects on menarche only when paternally inherited. Disproportionate effects of variants on early or late puberty timing are observed: single variant and heritability estimates are larger for early than late puberty timing in females. The opposite pattern is seen in males, with larger estimates for late than early puberty timing. Mendelian randomization analyses indicate causal inverse associations, independent of BMI, between puberty timing and risks for breast and endometrial cancers in women, and prostate cancer in men. In aggregate, our findings reveal new complexity in the genetic regulation of puberty timing and support new causal links with adult cancer risks. more...
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- 2016
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19. Evidence that lower socioeconomic position accentuates genetic susceptibility to obesity
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Z. Kutalik, Jess Tyrrell, Idris Guessous, George Davey Smith, Stéphane Joost, Michael N. Weedon, Beaumont Rn, Ruth Ks, Ryan M. Ames, Marcus A. Tuke, Hanieh Yaghootkar, Timothy M. Frayling, Rachel M. Freathy, Samuel E. Jones, David P. Strachan, Andrew R. Wood, and Anna Murray more...
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Socioeconomic position ,business.industry ,Sun protection ,Confounding ,030204 cardiovascular system & hematology ,medicine.disease ,Obesity ,03 medical and health sciences ,0302 clinical medicine ,Social deprivation ,Genetic predisposition ,Medicine ,030212 general & internal medicine ,Allele ,business ,Body mass index ,Demography - Abstract
Susceptibility to obesity in today’s environment has a strong genetic component. Lower socioeconomic position (SEP) is associated with a higher risk of obesity but it is not known if it accentuates genetic susceptibility to obesity. We aimed to use up to 120,000 individuals from the UK Biobank study to test the hypothesis that measures of socioeconomic position accentuate genetic susceptibility to obesity. We used the Townsend deprivation index (TDI) as the main measure of socioeconomic position, and a 69-variant genetic risk score (GRS) as a measure of genetic susceptibility to obesity. We also tested the hypothesis that interactions between BMI genetics and socioeconomic position would result in evidence of interaction with individual measures of the obesogenic environment and behaviours that correlate strongly with socioeconomic position, even if they have no obesogenic role. These measures included self-reported TV watching, diet and physical activity, and an objective measure of activity derived from accelerometers. We performed several negative control tests, including a simulated environment correlated with BMI but not TDI, and sun protection use. We found evidence of gene-environment interactions with TDI (Pinteraction=3×10−10) such that, within the group of 50% living in the most relatively deprived situations, carrying 10 additional BMI-raising alleles was associated with approximately 3.8 kg extra weight in someone 1.73m tall. In contrast, within the group of 50% living in the least deprivation, carrying 10 additional BMI-raising alleles was associated with approximately 2.9 kg extra weight. We also observed evidence of interaction between sun protection use and BMI genetics, suggesting that residual confounding may result in evidence of non-causal interactions. Our findings provide evidence that relative social deprivation best captures aspects of the obesogenic environment that accentuate the genetic predisposition to obesity in the UK. more...
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- 2016
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20. Large-scale genomic analyses link reproductive aging to hypothalamic signaling, breast cancer susceptibility and BRCA1-mediated DNA repair
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Day, FR, Ruth, KS, Thompson, DJ, Lunetta, KL, Pervjakova, N, Chasman, DI, Stolk, L, Finucane, HK, Sulem, P, Bulik-Sullivan, B, Esko, T, Johnson, AD, Elks, CE, Franceschini, N, He, C, Altmaier, E, Brody, JA, Franke, LL, EHuffman, J, Keller, MF, McArdle, PF, Nutile, T, Porcu, E, Robino, A, Rose, LM, Schick, UM, Smith, JA, Teumer, A, Traglia, M, Vuckovic, D, Yao, J, Zhao, W, Albrecht, E, Amin, N, Corre, T, Hottenga, JJ, Mangino, M, Smith, AV, Tanaka, T, Abecasis, GR, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Arndt, V, Arnold, AM, Barbieri, C, Beckmann, MW, Beeghly-Fadiel, A, Benitez, J, Bernstein, L, Bielinski, SJ, Blomqvist, C, Boerwinkle, E, Bogdanova, NV, Bojesen, SE, Bolla, MK, Borresen-Dale, AL, Boutin, TS, Brauch, H, Brenner, H, Brüning, T, Burwinkel, B, Campbell, A, Campbell, H, Chanock, SJ, Chapman, JR, Chen, YDI, Chenevix-Trench, G, and Couch, FJ more...
- Abstract
© 2015 Nature America, Inc. Menopause timing has a substantial impact on infertility and risk of disease, including breast cancer, but the underlying mechanisms are poorly understood. We report a dual strategy in -1/470,000 women to identify common and low-frequency protein-coding variation associated with age at natural menopause (ANM). We identified 44 regions with common variants, including two regions harboring additional rare missense alleles of large effect. We found enrichment of signals in or near genes involved in delayed puberty, highlighting the first molecular links between the onset and end of reproductive lifespan. Pathway analyses identified major association with DNA damage response (DDR) genes, including the first common coding variant in BRCA1 associated with any complex trait. Mendelian randomization analyses supported a causal effect of later ANM on breast cancer risk (-1/46% increase in risk per year; P = 3 × 10 -14), likely mediated by prolonged sex hormone exposure rather than DDR mechanisms. more...
- Published
- 2015
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21. Large-Scale Genomic Analyses Link Reproductive Aging to Hypothalamic Signaling, Breast Cancer Susceptibility, and BRCA1-Mediated DNA Repair EDITORIAL COMMENT
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Day, FR, Ruth, KS, Thompson, DJ, Lunetta, KL, Pervjakova, N, Chasman, DI, Stolk, Lisette, Finucane, HK, Sulem, P, Bulik-Sullivan, B, Esko, T, Johnson, AD, Elks, CE, Franceschini, N, He, C, Altmaier, E, Brody, JA, Franke, LL, Huffman, JE, Keller, MF, McArdle, PF, Nutile, T, Porcu, E, Robino, A, Rose, LM, Schick, UM, Smith, JA, Teumer, A, Traglia, M, Vuckovic, D, Yao, J, Zhao, W, Albrecht, E, Amin, Najaf, Corre, T, Hottenga, JJ (Jouke Jan), Mangino, M, Smith, AV, Tanaka, T, Abecasis, GR, Andrulis, IL, Anton-Culver, H, Antoniou, AC, Arndt, V, Arnold, AM, Barbieri, C, Beckmann, MW, Beeghly-Fadiel, A, Benitez, J, Bernstein, L, Bielinski, SJ, Blomqvist, C, Boerwinkle, E, Bogdanova, NV, Bojesen, SE, Bolla, MK, Borresen-Dale, AL, Boutin, TS, Brauch, H, Brenner, H, Bruning, T, Burwinkel, B, Campbell, A (Archie), Campbell, H, Chanock, SJ, Chapman, JR, Chen, YDI, Chenevix-Trench, G, Couch, FJ, Coviello, AD, Cox, A, Czene, K, Darabi, H, de Vivo, I, Demerath, EW, Dennis, J, Devilee, P, Dork, T, dos-Santos-Silva, I, Dunning, AM, Eicher, JD, Fasching, PA, Faul, JD, Figueroa, J, Flesch-Janys, D, Gandin, I, Garcia, ME, Garcia-Closas, M, Giles, GG, Girotto, GG, Goldberg, MS, Gonzalez-Neira, A, Goodarzi, MO, Grove, ML, Gudbjartsson, DF, Guenel, P, Guo, XQ, Haiman, CA, Hall, P, Hamann, U, Henderson, BE, Hocking, LJ, Hofman, Bert, Homuth, G, Hooning, Maartje, Hopper, JL, Hu, FB, Huang, JY, Humphreys, K, Hunter, DJ, Jakubowska, A, Jones, SE, Kabisch, M, Karasik, D, Knight, JA, Kolcic, I, Kooperberg, C, Kosma, VM, Kriebel, J, Kristensen, V, Lambrechts, D, Langenberg, C, Li, JM, Li, X, Lindstrom, S, Liu, YM, Luan, JA, Lubinski, J, Magi, R, Mannermaa, A, Manz, J, Margolin, S, Marten, J, Martin, NG, Masciullo, C, Meindl, A, Michailidou, K, Mihailov, E, Milani, L, Milne, RL, Muller-Nurasyid, M, Nalls, M, Neale, BM, Nevanlinna, H, Neven, P, Newman, AB, Nordestgaard, BG, Olson, JE, Padmanabhan, S, Peterlongo, P, Peters, U, Petersmann, A, Peto, J, Pharoah, PDP, Pirastu, NN, Pirie, A, Pistis, G, Polasek, O, Porteous, D, Psaty, BM, Pylkas, K, Radice, P, Raffel, LJ, Rivadeneira, Fernando, Rudan, I, Rudolph, A, Ruggiero, D, Sala, CF, Sanna, S, Sawyer, EJ, Schlessinger, D, Schmidt, MK (Marjanka), Schmidt, F, Schmutzler, RK, Schoemaker, MJ, Scott, RA, Seynaeve, Caroline, Simard, J, Sorice, R, Southey, MC, Stockl, D, Strauch, K, Swerdlow, A, Taylor, KD, Thorsteinsdottir, U, Toland, AE, Tomlinson, I, Truong, T, Tryggvadottir, L, Turner, ST, Vozzi, D, Wang, Q (Qing), Wellons, M, Willemsen, G, Wilson, JF, Winqvist, R, Wolffenbuttel, BBHR, Wright, AF, Yannoukakos, D, Zemunik, T, Zheng, W, Zygmunt, M, Bergmann, S, Boomsma, DI, Buring, JE, Ferrucci, L, Montgomery, GW, Gudnason, V, Spector, TD, Duijn, Cornelia, Alizadeh, BZ, Ciullo, M, Crisponi, L, Easton, DF, Gasparini, PP, Gieger, C, Harris, TB, Hayward, C, Kardia, SLR, Kraft, P, McKnight, B, Metspalu, A, Morrison, AC, Reiner, AP, Ridker, PM, Rotter, JI, Toniolo, D, Uitterlinden, André, Ulivi, S, Volzke, H, Wareham, NJ, Weir, DR, Yerges-Armstrong, LM, Price, AL, Stefansson, K, Visser, Jenny, Ong, KK, Chang-Claude, J, Murabito, JM, Perry, JRB, Murray, A, Systems Ecology, Neuroscience Campus Amsterdam - Neurobiology of Mental Health, Internal Medicine, Epidemiology, Medical Oncology, and Clinical Genetics more...
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SDG 3 - Good Health and Well-being - Published
- 2015
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22. Genome-Wide Association Analyses in 128,266 Individuals Identifies New Morningness and Sleep Duration Loci
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Jones, SE, Tyrrell, J, Wood, AR, Beaumont, RN, Ruth, KS, Tuke, MA, Yaghootkar, H, Hu, Y, Teder-Laving, M, Hayward, C, Roenneberg, T, Wilson, JF, Del Greco, F, Hicks, AA, Shin, C, Yun, CH, Lee, SK, Metspalu, A, Byrne, EM, Gehrman, PR, Tiemeier, Henning, Allebrandt, KV, Freathy, RM, Murray, A, Hinds, DA, Frayling, TM, Weedon, MN, Jones, SE, Tyrrell, J, Wood, AR, Beaumont, RN, Ruth, KS, Tuke, MA, Yaghootkar, H, Hu, Y, Teder-Laving, M, Hayward, C, Roenneberg, T, Wilson, JF, Del Greco, F, Hicks, AA, Shin, C, Yun, CH, Lee, SK, Metspalu, A, Byrne, EM, Gehrman, PR, Tiemeier, Henning, Allebrandt, KV, Freathy, RM, Murray, A, Hinds, DA, Frayling, TM, and Weedon, MN more...
- Abstract
Disrupted circadian rhythms and reduced sleep duration are associated with several human diseases, particularly obesity and type 2 diabetes, but until recently, little was known about the genetic factors influencing these heritable traits. We performed genome-wide association studies of self-reported chronotype (morning/evening person) and self-reported sleep duration in 128,266 white British individuals from the UK Biobank study. Sixteen variants were associated with chronotype (P<5x10(-8)), including variants near the known circadian rhythm genes RGS16 (1.21 odds of morningness, 95% CI [1.15, 1.27], P = 3x10(-12)) and PER2 (1.09 odds of morningness, 95% CI [1.06, 1.12], P = 4x10(-10)). The PER2 signal has previously been associated with iris function. We sought replication using self-reported data from 89,283 23andMe participants; thirteen of the chronotype signals remained associated at P<5x10(-8) on meta-analysis and eleven of these reached P< 0.05 in the same direction in the 23andMe study. We also replicated 9 additional variants identified when the 23andMe study was used as a discovery GWAS of chronotype (all P<0.05 and meta-analysis P<5x10(-8)). For sleep duration, we replicated one known signal in PAX8 (2.6 minutes per allele, 95% CI [1.9, 3.2], P = 5.7x10(-16)) and identified and replicated two novel associations at VRK2 (2.0 minutes per allele, 95% CI [1.3, 2.7], P = 1.2x10(-9); and 1.6 minutes per allele, 95% CI [1.1, 2.2], P = 7.6x10(-9)). Although we found genetic correlation between chronotype and BMI (rG = 0.056, P = 0.05); undersleeping and BMI (rG = 0.147, P = 1x10(-5)) and over-sleeping and BMI (rG = 0.097, P = 0.04), Mendelian Randomisation analyses, with limited power, provided no consistent evidence of causal associations between BMI or type 2 diabetes and chronotype or sleep duration. Our study brings the total number of loci associated with chronotype to 22 and with sleep duration to three, and provides new insights into the bi more...
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- 2016
23. Rare coding variants and X-linked loci associated with age at menarche
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Lunetta, KL, Day, FR, Sulem, P, Ruth, KS, Tung, JY, Hinds, DA, Esko, T, Elks, CE, Altmaier, E, He, CY, Huffman, JE, Mihailov, E, Porcu, E, Robino, A, Rose, LM, Schick, UM, Stolk, Lisette, Teumer, A, Thompson, DJ, Traglia, M, Wang, CA, Yerges-Armstrong, LM, Antoniou, AC, Barbieri, C, Coviello, AD, Cucca, F, Demerath, EW, Dunning, AM, Gandin, I, Grove, ML, Gudbjartsson, DF, Hocking, LJ, Hofman, Bert, Huang, JY, Jackson, RD, Karasik, D, Kriebel, J, Lange, Edmee, Lange, LA, Langenberg, C, Li, X, Luan, JA, Magi, R, Morrison, AC, Padmanabhan, S, Pirie, A, Polasek, O, Porteous, D, Reiner, AP, Rivadeneira, Fernando, Rudan, I, Sala, CF, Schlessinger, D, Scott, RA, Stockl, D, Visser, Jenny, Volker, U, Vozzi, D, Wilson, JG, Zygmunt, M, Boerwinkle, E, Buring, JE, Crisponi, L, Easton, DF, Hayward, C, Hu, FB, Liu, SM (Simin), Metspalu, A, Pennell, CE, Ridker, PM, Strauch, K, Streeten, EA, Toniolo, D, Uitterlinden, André, Ulivi, S, Volzke, H, Wareham, NJ, Wellons, M, Franceschini, N, Chasman, DI, Thorsteinsdottir, U, Murray, A, Stefansson, K, Murabito, JM, Ong, KK, Perry, JRB, Forouhi, NG, Kerrison, ND, Sharp, SJ, Sims, M, Barroso, I, Deloukas, P, McCarthy, MI, Arriola, L, Balkau, B, Barricarte, A, Boeing, H, Franks, PW, Gonzalez, C, Grioni, S, Kaaks, R, Key, TJ, Navarro, C, Nilsson, PM, Overvad, K, Palli, D, Panico, S, Quiros, JR, Rolandsson, O, Sacerdote, C, Sanchez, MJ (Maria-Jose), Slimani, N, Tjonneland, A, Tumino, R, van der A, DL, van der Schouw, YT, Riboli, E, Smith, BH, Campbell, A (Archie), Deary, IJ, McIntosh, AM, Lunetta, KL, Day, FR, Sulem, P, Ruth, KS, Tung, JY, Hinds, DA, Esko, T, Elks, CE, Altmaier, E, He, CY, Huffman, JE, Mihailov, E, Porcu, E, Robino, A, Rose, LM, Schick, UM, Stolk, Lisette, Teumer, A, Thompson, DJ, Traglia, M, Wang, CA, Yerges-Armstrong, LM, Antoniou, AC, Barbieri, C, Coviello, AD, Cucca, F, Demerath, EW, Dunning, AM, Gandin, I, Grove, ML, Gudbjartsson, DF, Hocking, LJ, Hofman, Bert, Huang, JY, Jackson, RD, Karasik, D, Kriebel, J, Lange, Edmee, Lange, LA, Langenberg, C, Li, X, Luan, JA, Magi, R, Morrison, AC, Padmanabhan, S, Pirie, A, Polasek, O, Porteous, D, Reiner, AP, Rivadeneira, Fernando, Rudan, I, Sala, CF, Schlessinger, D, Scott, RA, Stockl, D, Visser, Jenny, Volker, U, Vozzi, D, Wilson, JG, Zygmunt, M, Boerwinkle, E, Buring, JE, Crisponi, L, Easton, DF, Hayward, C, Hu, FB, Liu, SM (Simin), Metspalu, A, Pennell, CE, Ridker, PM, Strauch, K, Streeten, EA, Toniolo, D, Uitterlinden, André, Ulivi, S, Volzke, H, Wareham, NJ, Wellons, M, Franceschini, N, Chasman, DI, Thorsteinsdottir, U, Murray, A, Stefansson, K, Murabito, JM, Ong, KK, Perry, JRB, Forouhi, NG, Kerrison, ND, Sharp, SJ, Sims, M, Barroso, I, Deloukas, P, McCarthy, MI, Arriola, L, Balkau, B, Barricarte, A, Boeing, H, Franks, PW, Gonzalez, C, Grioni, S, Kaaks, R, Key, TJ, Navarro, C, Nilsson, PM, Overvad, K, Palli, D, Panico, S, Quiros, JR, Rolandsson, O, Sacerdote, C, Sanchez, MJ (Maria-Jose), Slimani, N, Tjonneland, A, Tumino, R, van der A, DL, van der Schouw, YT, Riboli, E, Smith, BH, Campbell, A (Archie), Deary, IJ, and McIntosh, AM more...
- Abstract
More than 100 loci have been identified for age at menarche by genome-wide association studies; however, collectively these explain only similar to 3% of the trait variance. Here we test two overlooked sources of variation in 192,974 European ancestry women: low-frequency proteincoding variants and X-chromosome variants. Five missense/nonsense variants (in ALMS1/LAMB2/TNRC6A/TACR3/PRKAG1) are associated with age at menarche (minor allele frequencies 0.08-4.6%; effect sizes 0.08-1.25 years per allele; P<5 x 10(-8)). In addition, we identify common X-chromosome loci at IGSF1 (rs762080, P = 9.4 x 10(-13)) and FAAH2 (rs5914101, P = 4.9 x 10(-10)). Highlighted genes implicate cellular energy homeostasis, post-transcriptional gene silencing and fatty-acid amide signalling. A frequently reported mutation in TACR3 for idiopathic hypogonatrophic hypogonadism (p.W275X) is associated with 1.25-year-later menarche (P = 2.8 x 10(-11)), illustrating the utility of population studies to estimate the penetrance of reportedly pathogenic mutations. Collectively, these novel variants explain similar to 0.5% variance, indicating that these overlooked sources of variation do not substantially explain the 'missing heritability' of this complex trait. more...
- Published
- 2015
24. GWAS Identifies Risk Locus for Erectile Dysfunction and Implicates Hypothalamic Neurobiology and Diabetes in Etiology
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Bovijn, J, Jackson, L, Censin, J, Chen, CY, Laisk, T, Laber, S, Ferreira, T, Pulit, SL, Glastonbury, CA, Smoller, JW, Harrison, JW, Ruth, KS, Beaumont, RN, Jones, SE, Tyrrell, J, Wood, AR, Weedon, MN, Mägi, R, Neale, B, Lindgren, CM, Murray, A, Holmes, MV, and 'European Union (EU)' and 'Horizon 2020' more...
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Male ,diabetes ,erectile dysfunction ,Hypothalamus ,impotence ,UK biobank ,mendelian randomisation ,Europe ,Repressor Proteins ,Diabetes Mellitus, Type 2 ,Report ,Basic Helix-Loop-Helix Transcription Factors ,genome-wide association ,Mendelian randomization ,Humans ,GWAS ,Chromosomes, Human, Pair 6 ,Computer Simulation ,Genetic Predisposition to Disease ,SIM1 ,Alleles ,Genome-Wide Association Study - Abstract
Erectile dysfunction (ED) is a common condition affecting more than 20% of men over 60 years, yet little is known about its genetic architecture. We performed a genome-wide association study of ED in 6,175 case subjects among 223,805 European men and identified one locus at 6q16.3 (lead variant rs57989773, OR 1.20 per C-allele; p = 5.71 × 10−14), located between MCHR2 and SIM1. In silico analysis suggests SIM1 to confer ED risk through hypothalamic dysregulation. Mendelian randomization provides evidence that genetic risk of type 2 diabetes mellitus is a cause of ED (OR 1.11 per 1-log unit higher risk of type 2 diabetes). These findings provide insights into the biological underpinnings and the causes of ED and may help prioritize the development of future therapies for this common disorder. more...
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25. Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk
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Day, FR, Thompson, DJ, Helgason, H, Chasman, DI, Finucane, H, Sulem, P, Ruth, KS, Whalen, S, Sarkar, AK, Albrecht, E, Altmaier, E, Amini, M, Barbieri, CM, Boutin, T, Campbell, A, Demerath, E, Giri, A, He, C, Hottenga, JJ, Karlsson, R, Kolcic, I, Loh, P-R, Lunetta, KL, Mangino, M, Marco, B, McMahon, G, Medland, SE, Nolte, IM, Noordam, R, Nutile, T, Paternoster, L, Perjakova, N, Porcu, E, Rose, LM, Schraut, KE, Segrè, AV, Smith, AV, Stolk, L, Teumer, A, Andrulis, IL, Bandinelli, S, Beckmann, MW, Benitez, J, Bergmann, S, Bochud, M, Boerwinkle, E, Bojesen, SE, Bolla, MK, Brand, JS, Brauch, H, Brenner, H, Broer, L, Brüning, T, Buring, JE, Campbell, H, Catamo, E, Chanock, S, Chenevix-Trench, G, Corre, T, Couch, FJ, Cousminer, DL, Cox, A, Crisponi, L, Czene, K, Davey Smith, G, De Geus, EJCN, De Mutsert, R, De Vivo, I, Dennis, J, Devilee, P, Dos-Santos-Silva, I, Dunning, AM, Eriksson, JG, Fasching, PA, Fernández-Rhodes, L, Ferrucci, L, Flesch-Janys, D, Franke, L, Gabrielson, M, Gandin, I, Giles, GG, Grallert, H, Gudbjartsson, DF, Guénel, P, Hall, P, Hallberg, E, Hamann, U, Harris, TB, Hartman, CA, Heiss, G, Hooning, MJ, Hopper, JL, Hu, F, Hunter, DJ, Ikram, MA, Im, HK, Järvelin, M-R, Joshi, PK, Karasik, D, Kellis, M, Kutalik, Z, LaChance, G, Lambrechts, D, Langenberg, C, Launer, LJ, Laven, JSE, Lenarduzzi, S, Li, J, Lind, PA, Lindstrom, S, Liu, Y, Luan, J, Mägi, R, Mannermaa, A, Mbarek, H, McCarthy, MI, Meisinger, C, Meitinger, T, Menni, C, Metspalu, A, Michailidou, K, Milani, L, Milne, RL, Montgomery, GW, Mulligan, AM, Nalls, MA, Navarro, P, Nevanlinna, H, Nyholt, DR, Oldehinkel, AJ, O'Mara, TA, Padmanabhan, S, Palotie, A, Pedersen, N, Peters, A, Peto, J, Pharoah, PDP, Pouta, A, Radice, P, Rahman, I, Ring, SM, Robino, A, Rosendaal, FR, Rudan, I, Rueedi, R, Ruggiero, D, Sala, CF, Schmidt, MK, Scott, RA, Shah, M, Sorice, R, Southey, MC, Sovio, U, Stampfer, M, Steri, M, Strauch, K, Tanaka, T, Tikkanen, E, Timpson, NJ, Traglia, M, Truong, T, Tyrer, JP, Uitterlinden, AG, Edwards, DRV, Vitart, V, Völker, U, Vollenweider, P, Wang, Q, Widen, E, Van Dijk, KW, Willemsen, G, Winqvist, R, Wolffenbuttel, BHR, Zhao, JH, Zoledziewska, M, Zygmunt, M, Alizadeh, BZ, Boomsma, DI, Ciullo, M, Cucca, F, Esko, T, Franceschini, N, Gieger, C, Gudnason, V, Hayward, C, Kraft, P, Lawlor, DA, Magnusson, PKE, Martin, NG, Mook-Kanamori, DO, Nohr, EA, Polasek, O, Porteous, D, Price, AL, Ridker, PM, Snieder, H, Spector, TD, Stöckl, D, Toniolo, D, Ulivi, S, Visser, JA, Völzke, H, Wareham, NJ, Wilson, JF, LifeLines Cohort Study, InterAct Consortium, KConFab/AOCS Investigators, Endometrial Cancer Association Consortium, Ovarian Cancer Association Consortium, PRACTICAL Consortium, Spurdle, AB, Thorsteindottir, U, Pollard, KS, Easton, DF, Tung, JY, Chang-Claude, J, Hinds, D, Murray, A, Murabito, JM, Stefansson, K, Ong, KK, and Perry, JRB more...
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2. Zero hunger ,genome-wide association studies ,cancer ,reproductive disorders ,3. Good health - Abstract
The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project–imputed genotype data in up to ~370,000 women, we identify 389 independent signals (P < 5 × 10$^{−8}$) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain ~7.4% of the population variance in age at menarche, corresponding to ~25% of the estimated heritability. We implicate ~250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility. more...
26. Genome-wide associations for birth weight and correlations with adult disease
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Horikoshi, M, Beaumont, RN, Day, FR, Warrington, NM, Kooijman, MN, Fernandez-Tajes, J, Feenstra, B, Van Zuydam, NR, Gaulton, KJ, Grarup, N, Bradfield, JP, Strachan, DP, Li-Gao, R, Ahluwalia, TS, Kreiner, E, Rueedi, R, Lyytikäinen, L-P, Cousminer, DL, Wu, Y, Thiering, E, Wang, CA, Have, CT, Hottenga, J-J, Vilor-Tejedor, N, Joshi, PK, Boh, ETH, Ntalla, I, Pitkänen, N, Mahajan, A, Van Leeuwen, EM, Joro, R, Lagou, V, Nodzenski, M, Diver, LA, Zondervan, KT, Bustamante, M, Marques-Vidal, P, Mercader, JM, Bennett, AJ, Rahmioglu, N, Nyholt, DR, Ma, RCW, Tam, CHT, Tam, WH, CHARGE Consortium Hematology Working Group, Ganesh, SK, Van Rooij, FJA, Jones, SE, Loh, P-R, Ruth, KS, Tuke, MA, Tyrrell, J, Wood, AR, Yaghootkar, H, Scholtens, DM, Paternoster, L, Prokopenko, I, Kovacs, P, Atalay, M, Willems, SM, Panoutsopoulou, K, Wang, X, Carstensen, L, Geller, F, Schraut, KE, Murcia, M, Van Beijsterveldt, CEM, Willemsen, G, Appel, EVR, Fonvig, CE, Trier, C, Tiesler, CMT, Standl, M, Kutalik, Z, Bonàs-Guarch, S, Hougaard, DM, Sánchez, F, Torrents, D, Waage, J, Hollegaard, MV, De Haan, HG, Rosendaal, FR, Medina-Gomez, C, Ring, SM, Hemani, G, McMahon, G, Robertson, NR, Groves, CJ, Langenberg, C, Luan, J, Scott, RA, Zhao, JH, Mentch, FD, MacKenzie, SM, Reynolds, RM, Early Growth Genetics (EGG) Consortium, Lowe, WL, Tönjes, A, Stumvoll, M, Lindi, V, Lakka, TA, Van Duijn, CM, Kiess, W, Körner, A, Sørensen, TIA, Niinikoski, H, Pahkala, K, Raitakari, OT, Zeggini, E, Dedoussis, GV, Teo, Y-Y, Saw, S-M, Melbye, M, Campbell, H, Wilson, JF, Vrijheid, M, De Geus, EJCN, Boomsma, DI, Kadarmideen, HN, Holm, J-C, Hansen, T, Sebert, S, Hattersley, AT, Beilin, LJ, Newnham, JP, Pennell, CE, Heinrich, J, Adair, LS, Borja, JB, Mohlke, KL, Eriksson, JG, Widén, E, Kähönen, M, Viikari, JS, Lehtimäki, T, Vollenweider, P, Bønnelykke, K, Bisgaard, H, Mook-Kanamori, DO, Hofman, A, Rivadeneira, F, Uitterlinden, AG, Pisinger, C, Pedersen, O, Power, C, Hyppönen, E, Wareham, NJ, Hakonarson, H, Davies, E, Walker, BR, Jaddoe, VWV, Järvelin, M-R, Grant, SFA, Vaag, AA, Lawlor, DA, Frayling, TM, Smith, GD, Morris, AP, Ong, KK, Felix, JF, Timpson, NJ, Perry, JRB, Evans, DM, McCarthy, MI, and Freathy, RM more...
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quantitative trait ,hypertension ,intrauterine growth ,genome-wide association studies ,metabolic disorders ,3. Good health - Abstract
Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW ($\textit{P}$ < 5 × 10$^{-8}$). Overall, approximately 15% of variance in BW was captured by assays of fetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure ($\textit{R}$ $_{g}$ = -0.22, $\textit{P}$ = 5.5 × 10$^{-13}$), T2D ($\textit{R}$ $_{g}$ = -0.27, $\textit{P}$ = 1.1 × 10$^{-6}$) and coronary artery disease ($\textit{R}$ $_{g}$ = -0.30, $\textit{P}$ = 6.5 × 10$^{-9}$). In addition, using large -cohort datasets, we demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions ($\textit{P}$ = 1.9 × 10$^{-4}$). We demonstrate that life-course associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and identify some of the pathways through which these causal genetic effects are mediated. more...
27. Colorectal cancer risk stratification using a polygenic risk score in symptomatic primary care patients-a UK Biobank retrospective cohort study.
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Mallabar-Rimmer B, Merriel SWD, Webster AP, Jackson L, Wood AR, Barclay M, Tyrrell J, Ruth KS, Thirlwell C, Oram R, Weedon MN, Bailey SER, and Green HD
- Subjects
- Humans, Female, Male, Middle Aged, Aged, United Kingdom epidemiology, Retrospective Studies, Adult, Risk Assessment methods, Early Detection of Cancer methods, Biological Specimen Banks, Risk Factors, Genetic Risk Score, UK Biobank, Colorectal Neoplasms genetics, Colorectal Neoplasms diagnosis, Primary Health Care, Multifactorial Inheritance
- Abstract
Colorectal cancer (CRC) is a leading cause of cancer mortality worldwide. Accurate cancer risk assessment approaches could increase rates of early CRC diagnosis, improve health outcomes for patients and reduce pressure on diagnostic services. The faecal immunochemical test (FIT) for blood in stool is widely used in primary care to identify symptomatic patients with likely CRC. However, there is a 6-16% noncompliance rate with FIT in clinic and ~90% of patients over the symptomatic 10 µg/g test threshold do not have CRC. A polygenic risk score (PRS) quantifies an individual's genetic risk of a condition based on many common variants. Existing PRS for CRC have so far been used to stratify asymptomatic populations. We conducted a retrospective cohort study of 50,387 UK Biobank participants with a CRC symptom in their primary care record at age 40+. A PRS based on 201 variants, 5 genetic principal components and 22 other risk factors and markers for CRC were assessed for association with CRC diagnosis within 2 years of first symptom presentation using logistic regression. Associated variables were included in an integrated risk model and trained in 80% of the cohort to predict CRC diagnosis within 2 years. An integrated risk model combining PRS, age, sex, and patient-reported symptoms was predictive of CRC development in a testing cohort (receiver operating characteristic area under the curve, ROCAUC: 0.76, 95% confidence interval: 0.71-0.81). This model has the potential to improve early diagnosis of CRC, particularly in cases of patient noncompliance with FIT., Competing Interests: Competing interests The authors declare no competing interests. Ethical approval Data from the UK Biobank Resource were accessed under Application Number 74981. UK Biobank was approved as tissue bank resource by North West Multi-centre Research Ethics Committee. All UK Biobank participants gave written informed consent for use of their data for health research. Participants who withdrew consent during this study were excluded from analysis., (© 2024. The Author(s).) more...
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- 2024
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28. Genetic links between ovarian ageing, cancer risk and de novo mutation rates.
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Stankovic S, Shekari S, Huang QQ, Gardner EJ, Ivarsdottir EV, Owens NDL, Mavaddat N, Azad A, Hawkes G, Kentistou KA, Beaumont RN, Day FR, Zhao Y, Jonsson H, Rafnar T, Tragante V, Sveinbjornsson G, Oddsson A, Styrkarsdottir U, Gudmundsson J, Stacey SN, Gudbjartsson DF, Kennedy K, Wood AR, Weedon MN, Ong KK, Wright CF, Hoffmann ER, Sulem P, Hurles ME, Ruth KS, Martin HC, Stefansson K, Perry JRB, and Murray A more...
- Subjects
- Adult, Female, Humans, Male, Middle Aged, DNA Damage genetics, Fertility genetics, Genetic Variation genetics, Genome, Human genetics, Germ-Line Mutation genetics, Menarche genetics, Time Factors, UK Biobank, United Kingdom epidemiology, Aging genetics, Aging pathology, Genetic Predisposition to Disease genetics, Menopause genetics, Mutation Rate, Neoplasms genetics, Ovary metabolism, Ovary pathology
- Abstract
Human genetic studies of common variants have provided substantial insight into the biological mechanisms that govern ovarian ageing
1 . Here we report analyses of rare protein-coding variants in 106,973 women from the UK Biobank study, implicating genes with effects around five times larger than previously found for common variants (ETAA1, ZNF518A, PNPLA8, PALB2 and SAMHD1). The SAMHD1 association reinforces the link between ovarian ageing and cancer susceptibility1 , with damaging germline variants being associated with extended reproductive lifespan and increased all-cause cancer risk in both men and women. Protein-truncating variants in ZNF518A are associated with shorter reproductive lifespan-that is, earlier age at menopause (by 5.61 years) and later age at menarche (by 0.56 years). Finally, using 8,089 sequenced trios from the 100,000 Genomes Project (100kGP), we observe that common genetic variants associated with earlier ovarian ageing associate with an increased rate of maternally derived de novo mutations. Although we were unable to replicate the finding in independent samples from the deCODE study, it is consistent with the expected role of DNA damage response genes in maintaining the genetic integrity of germ cells. This study provides evidence of genetic links between age of menopause and cancer risk., (© 2024. The Author(s).) more...- Published
- 2024
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29. Response to Penetrance estimates of hereditary cancers in a population setting using UK Biobank data.
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Jackson L, Weedon MN, Green HD, Mallabar-Rimmer B, Harrison JW, Wood AR, Ruth KS, Tyrrell J, and Wright CF
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- 2024
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30. Menopause age, reproductive span and hormone therapy duration predict the volume of medial temporal lobe brain structures in postmenopausal women.
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Steventon JJ, Lancaster TM, Baker ES, Bracher-Smith M, Escott-Price V, Ruth KS, Davies W, Caseras X, and Murphy K
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- Humans, Female, Duration of Therapy, Temporal Lobe pathology, Menopause, Magnetic Resonance Imaging, Estrogens, Estradiol, Postmenopause, Alzheimer Disease pathology
- Abstract
Medial temporal lobe (MTL) atrophy is correlated with risk and severity of Alzheimer disease (AD) pathology and cognitive decline. Increasing evidence suggest that oestrogens affect the aging of MTL structures. Here we investigate the relationship between reproductive hormone exposure, polygenic scores for AD risk and oestradiol concentration, MTL anatomy and cognitive performance in postmenopausal women. To this end, we used data from 10,924 female participants in the UK Biobank from whom brain MRI and genetic data were available. We fitted linear regression models to test whether the volume of structures comprising the MTL were predicted by a) timing related to menopause, b) the use and timing of hormone replacement therapy (HRT) and c) polygenic scores for AD risk and oestradiol concentration. Results showed that longer use of HRT was associated with larger parahippocampal volumes (2.53 mm
3 /year, p = 0.042). A later age of natural menopause, and a longer reproductive span, was associated with larger hippocampal (6.08 and 5.72 mm3 /year, p = 0.0006 and 0.0005), parahippocampal (4.17 mm3 and 4.19 mm3 /year, p = 0.00006 and 0.00001), amygdala (2.10 and 2.22 mm3 /year, p = 0.028 and 0.01) and perirhinal cortical (2.56 and 2.95 mm3 /year, p = 0.028 and 0.008) volumes. Superior prospective memory performance was associated with later age at natural menopause, and a longer reproductive span (ß = 0.05 and 0.05 respectively, p = 0.019 and 0.019). Polygenic scores for AD risk and for oestradiol concentration were not associated with MTL volume and did not interact with menopause-related factors to affect MTL structure. Our results suggest that HRT use did not have any detrimental effects on cognition or brain structure, whilst greater exposure to reproductive hormones across time is associated both with slightly larger volumes of specific MTL structures and marginally superior memory performance, independent of genetic risk for AD and genetic predisposition for higher oestradiol levels. However, the clinical utility of maintenance of oestrogens post-menopause for brain health and protection against cognitive decline is curtailed by the small effect sizes observed., Competing Interests: Declaration of Competing Interest The authors report no conflicting interests., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.) more...- Published
- 2023
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31. Insights into the genetics of menopausal vasomotor symptoms: genome-wide analyses of routinely-collected primary care health records.
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Ruth KS, Beaumont RN, Locke JM, Tyrrell J, Crandall CJ, Hawkes G, Frayling TM, Prague JK, Patel KA, Wood AR, Weedon MN, and Murray A
- Subjects
- Female, Humans, Quality of Life, Cross-Sectional Studies, Menopause genetics, Primary Health Care, Genome-Wide Association Study, Hot Flashes genetics
- Abstract
Background: Vasomotor symptoms (VMS) can often significantly impact women's quality of life at menopause. In vivo studies have shown that increased neurokinin B (NKB) / neurokinin 3 receptor (NK3R) signalling contributes to VMS, with previous genetic studies implicating the TACR3 gene locus that encodes NK3R. Large-scale genomic analyses offer the possibility of biological insights but few such studies have collected data on VMS, while proxy phenotypes such as hormone replacement therapy (HRT) use are likely to be affected by changes in clinical practice. We investigated the genetic basis of VMS by analysing routinely-collected health records., Methods: We performed a GWAS of VMS derived from linked primary-care records and cross-sectional self-reported HRT use in up to 153,152 women from UK Biobank, a population-based cohort. In a subset of this cohort (n = 39,356), we analysed exome-sequencing data to test the association with VMS of rare deleterious genetic variants. Finally, we used Mendelian randomisation analysis to investigate the reasons for HRT use over time., Results: Our GWAS of health-records derived VMS identified a genetic signal near TACR3 associated with a lower risk of VMS (OR=0.76 (95% CI 0.72,0.80) per A allele, P=3.7x10
-27 ), which was consistent with previous studies, validating this approach. Conditional analyses demonstrated independence of genetic signals for puberty timing and VMS at the TACR3 locus, including a rare variant predicted to reduce functional NK3R levels that was associated with later menarche (P = 5 × 10-9 ) but showed no association with VMS (P = 0.6). Younger menopause age was causally-associated with greater HRT use before 2002 but not after., Conclusions: We provide support for TACR3 in the genetic basis of VMS but unexpectedly find that rare genomic variants predicted to lower NK3R levels did not modify VMS, despite the proven efficacy of NK3R antagonists. Using genomics we demonstrate changes in genetic associations with HRT use over time, arising from a change in clinical practice since the early 2000s, which is likely to reflect a switch from preventing post-menopausal complications in women with earlier menopause to primarily treating VMS. Our study demonstrates that integrating routinely-collected primary care health records and genomic data offers great potential for exploring the genetic basis of symptoms., (© 2023. BioMed Central Ltd., part of Springer Nature.) more...- Published
- 2023
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32. Influence of family history on penetrance of hereditary cancers in a population setting.
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Jackson L, Weedon MN, Green HD, Mallabar-Rimmer B, Harrison JW, Wood AR, Ruth KS, Tyrrell J, and Wright CF
- Abstract
Background: We sought to investigate how penetrance of familial cancer syndromes varies with family history using a population-based cohort., Methods: We analysed 454,712 UK Biobank participants with exome sequence and clinical data (data collected between March 2006 and June 2021). We identified participants with a self-reported family history of breast or colorectal cancer and a pathogenic/likely pathogenic variant in the major genes responsible for hereditary breast cancer or Lynch syndrome. We calculated survival to cancer diagnosis (controlled for sex, death, recruitment centre, screening and prophylactic surgery)., Findings: Women with a pathogenic BRCA1 or BRCA2 variant had an increased risk of breast cancer that was higher in those with a first-degree family history (relative hazard 10.3 and 7.8, respectively) than those without (7.2 and 4.7). Penetrance to age 60 was also higher in those with a family history (44.7%, CI 32.2-59.3 and 24.1%, CI 17.5-32.6) versus those without (22.8%, CI 15.9-32.0 and 17.9%, CI 13.8-23.0). A similar pattern was seen in Lynch syndrome: individuals with a pathogenic MLH1 , MSH2 or MSH6 variant had an increased risk of colorectal cancer that was significantly higher in those with a family history (relative hazard 35.6, 48.0 and 9.9) than those without (13.0, 15.4 and 7.2). Penetrance to age 60 was also higher for carriers of a pathogenic MLH1 or MSH2 variant in those with a family history (30.9%, CI 18.1-49.3 and 38.3%, CI 21.5-61.8) versus those without (20.5% CI 9.6-40.5 and 8.3% CI 2.1-30.4), but not for MSH6 (6.5% CI 2.7-15.1 with family history versus 8.3%, CI 5.1-13.2). Relative risk increases were also observed both within and across conditions., Interpretation: Individuals with pathogenic cancer syndrome variants may be at a less elevated risk of cancer in the absence of a first-degree family history, so in the context of results return, family history should be considered when counselling patients on the risks and benefits of potential follow-up care., Funding: The current work is supported by the MRC (grant no MR/T00200X/1). The MRC had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication., Competing Interests: The authors declare no competing interests., (© 2023 The Authors. Published by Elsevier Ltd.) more...
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- 2023
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33. Penetrance of pathogenic genetic variants associated with premature ovarian insufficiency.
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Shekari S, Stankovic S, Gardner EJ, Hawkes G, Kentistou KA, Beaumont RN, Mörseburg A, Wood AR, Prague JK, Mishra GD, Day FR, Baptista J, Wright CF, Weedon MN, Hoffmann ER, Ruth KS, Ong KK, Perry JRB, and Murray A more...
- Subjects
- Female, Humans, Adult, Penetrance, Basic Helix-Loop-Helix Transcription Factors genetics, Primary Ovarian Insufficiency genetics, Primary Ovarian Insufficiency complications, Primary Ovarian Insufficiency pathology, Menopause, Premature genetics
- Abstract
Premature ovarian insufficiency (POI) affects 1% of women and is a leading cause of infertility. It is often considered to be a monogenic disorder, with pathogenic variants in ~100 genes described in the literature. We sought to systematically evaluate the penetrance of variants in these genes using exome sequence data in 104,733 women from the UK Biobank, 2,231 (1.14%) of whom reported at natural menopause under the age of 40 years. We found limited evidence to support any previously reported autosomal dominant effect. For nearly all heterozygous effects on previously reported POI genes, we ruled out even modest penetrance, with 99.9% (13,699 out of 13,708) of all protein-truncating variants found in reproductively healthy women. We found evidence of haploinsufficiency effects in several genes, including TWNK (1.54 years earlier menopause, P = 1.59 × 10
-6 ) and SOHLH2 (3.48 years earlier menopause, P = 1.03 × 10-4 ). Collectively, our results suggest that, for the vast majority of women, POI is not caused by autosomal dominant variants either in genes previously reported or currently evaluated in clinical diagnostic panels. Our findings, plus previous studies, suggest that most POI cases are likely oligogenic or polygenic in nature, which has important implications for future clinical genetic studies, and genetic counseling for families affected by POI., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.) more...- Published
- 2023
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34. Response to: Genetic risk scores may compound rather than solve the issue of prostate cancer overdiagnosis (BJC-LT3342090).
- Author
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Green HD, Merriel SWD, Oram RA, Ruth KS, Tyrrell J, Jones SE, Thirlwell C, Weedon MN, and Bailey SER
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- Male, Humans, Prostate-Specific Antigen, Risk Factors, Early Detection of Cancer, Medical Overuse, Mass Screening, Overdiagnosis, Prostatic Neoplasms diagnosis
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- 2023
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35. Genetically proxied therapeutic prolyl-hydroxylase inhibition and cardiovascular risk.
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Harlow CE, Patel VV, Waterworth DM, Wood AR, Beaumont RN, Ruth KS, Tyrrell J, Oguro-Ando A, Chu AY, and Frayling TM
- Subjects
- Humans, Genome-Wide Association Study, Risk Factors, Prolyl Hydroxylases genetics, Genetic Predisposition to Disease, Heart Disease Risk Factors, Mendelian Randomization Analysis, Cardiovascular Diseases genetics, Stroke genetics
- Abstract
Prolyl hydroxylase (PHD) inhibitors are in clinical development for anaemia in chronic kidney disease. Epidemiological studies have reported conflicting results regarding safety of long-term therapeutic haemoglobin (Hgb) rises through PHD inhibition on risk of cardiovascular disease. Genetic variation in genes encoding PHDs can be used as partial proxies to investigate the potential effects of long-term Hgb rises. We used Mendelian randomization to investigate the effect of long-term Hgb level rises through genetically proxied PHD inhibition on coronary artery disease (CAD: 60 801 cases; 123 504 controls), myocardial infarction (MI: 42 561 cases; 123 504 controls) or stroke (40 585 cases; 406 111 controls). To further characterize long-term effects of Hgb level rises, we performed a phenome-wide association study (PheWAS) in up to 451 099 UK Biobank individuals. Genetically proxied therapeutic PHD inhibition, equivalent to a 1.00 g/dl increase in Hgb levels, was not associated (at P < 0.05) with increased odds of CAD; odd ratio (OR) [95% confidence intervals (CI)] = 1.06 (0.84, 1.35), MI [OR (95% CI) = 1.02 (0.79, 1.33)] or stroke [OR (95% CI) = 0.91 (0.66, 1.24)]. PheWAS revealed associations with blood related phenotypes consistent with EGLN's role, relevant kidney- and liver-related biomarkers like estimated glomerular filtration rate and microalbuminuria, and non-alcoholic fatty liver disease (Bonferroni-adjusted P < 5.42E-05) but these were not clinically meaningful. These findings suggest that long-term alterations in Hgb through PHD inhibition are unlikely to substantially increase cardiovascular disease risk; using large disease genome-wide association study data, we could exclude ORs of 1.35 for cardiovascular risk with a 1.00 g/dl increase in Hgb., (© The Author(s) 2022. Published by Oxford University Press.) more...
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- 2023
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36. Applying a genetic risk score for prostate cancer to men with lower urinary tract symptoms in primary care to predict prostate cancer diagnosis: a cohort study in the UK Biobank.
- Author
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Green HD, Merriel SWD, Oram RA, Ruth KS, Tyrrell J, Jones SE, Thirlwell C, Weedon MN, and Bailey SER
- Subjects
- Biological Specimen Banks, Cohort Studies, Genome-Wide Association Study, Humans, Male, Primary Health Care, Risk Factors, United Kingdom epidemiology, Lower Urinary Tract Symptoms diagnosis, Lower Urinary Tract Symptoms epidemiology, Lower Urinary Tract Symptoms etiology, Prostatic Neoplasms diagnosis, Prostatic Neoplasms epidemiology, Prostatic Neoplasms genetics
- Abstract
Background: Prostate cancer is highly heritable, with >250 common variants associated in genome-wide association studies. It commonly presents with non-specific lower urinary tract symptoms that are frequently associated with benign conditions., Methods: Cohort study using UK Biobank data linked to primary care records. Participants were men with a record showing a general practice consultation for a lower urinary tract symptom. The outcome measure was prostate cancer diagnosis within 2 years of consultation. The predictor was a genetic risk score of 269 genetic variants for prostate cancer., Results: A genetic risk score (GRS) is associated with prostate cancer in symptomatic men (OR per SD increase = 2.12 [1.86-2.41] P = 3.5e-30). An integrated risk model including age and GRS applied to symptomatic men predicted prostate cancer (AUC 0.768 [0.739-0.796]). Prostate cancer incidence was 8.1% (6.7-9.7) in the highest risk quintile. In the lowest quintile, prostate cancer incidence was <1%., Conclusions: This study is the first to apply GRS in primary care to improve the triage of symptomatic patients. Men with the lowest genetic risk of developing prostate cancer could safely avoid invasive investigation, whilst those identified with the greatest risk could be fast-tracked for further investigation. These results show that a GRS has potential application to improve the diagnostic pathway of symptomatic patients in primary care., (© 2022. The Author(s).) more...
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- 2022
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37. Detection and characterization of male sex chromosome abnormalities in the UK Biobank study.
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Zhao Y, Gardner EJ, Tuke MA, Zhang H, Pietzner M, Koprulu M, Jia RY, Ruth KS, Wood AR, Beaumont RN, Tyrrell J, Jones SE, Lango Allen H, Day FR, Langenberg C, Frayling TM, Weedon MN, Perry JRB, Ong KK, and Murray A more...
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- Biological Specimen Banks, Humans, Male, Sex Chromosome Aberrations, United Kingdom epidemiology, XYY Karyotype, Diabetes Mellitus, Type 2, Klinefelter Syndrome diagnosis, Klinefelter Syndrome epidemiology, Klinefelter Syndrome genetics
- Abstract
Purpose: The study aimed to systematically ascertain male sex chromosome abnormalities, 47,XXY (Klinefelter syndrome [KS]) and 47,XYY, and characterize their risks of adverse health outcomes., Methods: We analyzed genotyping array or exome sequence data in 207,067 men of European ancestry aged 40 to 70 years from the UK Biobank and related these to extensive routine health record data., Results: Only 49 of 213 (23%) of men whom we identified with KS and only 1 of 143 (0.7%) with 47,XYY had a diagnosis of abnormal karyotype on their medical records or self-report. We observed expected associations for KS with reproductive dysfunction (late puberty: risk ratio [RR] = 2.7; childlessness: RR = 4.2; testosterone concentration: RR = -3.8 nmol/L, all P < 2 × 10
-8 ), whereas XYY men appeared to have normal reproductive function. Despite this difference, we identified several higher disease risks shared across both KS and 47,XYY, including type 2 diabetes (RR = 3.0 and 2.6, respectively), venous thrombosis (RR = 6.4 and 7.4, respectively), pulmonary embolism (RR = 3.3 and 3.7, respectively), and chronic obstructive pulmonary disease (RR = 4.4 and 4.6, respectively) (all P < 7 × 10-6 )., Conclusion: KS and 47,XYY were mostly unrecognized but conferred substantially higher risks for metabolic, vascular, and respiratory diseases, which were only partially explained by higher levels of body mass index, deprivation, and smoking., Competing Interests: Conflict of Interest The authors declare no conflicts of interest., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.) more...- Published
- 2022
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38. Genome-wide association study meta-analysis identifies three novel loci for circulating anti-Müllerian hormone levels in women.
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Verdiesen RMG, van der Schouw YT, van Gils CH, Verschuren WMM, Broekmans FJM, Borges MC, Gonçalves Soares AL, Lawlor DA, Eliassen AH, Kraft P, Sandler DP, Harlow SD, Smith JA, Santoro N, Schoemaker MJ, Swerdlow AJ, Murray A, Ruth KS, and Onland-Moret NC more...
- Subjects
- Canada, Cohort Studies, Female, Humans, Nuclear Proteins, Anti-Mullerian Hormone blood, Anti-Mullerian Hormone genetics, Breast Neoplasms, Genome-Wide Association Study
- Abstract
Study Question: Can additional genetic variants for circulating anti-Müllerian hormone (AMH) levels be identified through a genome-wide association study (GWAS) meta-analysis including a large sample of premenopausal women?, Summary Answer: We identified four loci associated with AMH levels at P < 5 × 10-8: the previously reported MCM8 locus and three novel signals in or near AMH, TEX41 and CDCA7., What Is Known Already: AMH is expressed by antral stage ovarian follicles in women, and variation in age-specific circulating AMH levels has been associated with disease outcomes. However, the physiological mechanisms underlying these AMH-disease associations are largely unknown., Study Design, Size, Duration: We performed a GWAS meta-analysis in which we combined summary statistics of a previous AMH GWAS with GWAS data from 3705 additional women from three different cohorts., Participants/materials, Setting, Methods: In total, we included data from 7049 premenopausal female participants of European ancestry. The median age of study participants ranged from 15.3 to 48 years across cohorts. Circulating AMH levels were measured in either serum or plasma samples using different ELISA assays. Study-specific analyses were adjusted for age at blood collection and population stratification, and summary statistics were meta-analysed using a standard error-weighted approach. Subsequently, we functionally annotated GWAS variants that reached genome-wide significance (P < 5 × 10-8). We also performed a gene-based GWAS, pathway analysis and linkage disequilibrium score regression and Mendelian randomization (MR) analyses., Main Results and the Role of Chance: We identified four loci associated with AMH levels at P < 5 × 10-8: the previously reported MCM8 locus and three novel signals in or near AMH, TEX41 and CDCA7. The strongest signal was a missense variant in the AMH gene (rs10417628). Most prioritized genes at the other three identified loci were involved in cell cycle regulation. Genetic correlation analyses indicated a strong positive correlation among single nucleotide polymorphisms for AMH levels and for age at menopause (rg = 0.82, FDR = 0.003). Exploratory two-sample MR analyses did not support causal effects of AMH on breast cancer or polycystic ovary syndrome risk, but should be interpreted with caution as they may be underpowered and the validity of genetic instruments could not be extensively explored., Large Scale Data: The full AMH GWAS summary statistics will made available after publication through the GWAS catalog (https://www.ebi.ac.uk/gwas/)., Limitations, Reasons for Caution: Whilst this study doubled the sample size of the most recent GWAS, the statistical power is still relatively low. As a result, we may still lack power to identify more genetic variants for AMH and to determine causal effects of AMH on, for example, breast cancer. Also, follow-up studies are needed to investigate whether the signal for the AMH gene is caused by reduced AMH detection by certain assays instead of actual lower circulating AMH levels., Wider Implications of the Findings: Genes mapped to the MCM8, TEX41 and CDCA7 loci are involved in the cell cycle and processes such as DNA replication and apoptosis. The mechanism underlying their associations with AMH may affect the size of the ovarian follicle pool. Altogether, our results provide more insight into the biology of AMH and, accordingly, the biological processes involved in ovarian ageing., Study Funding/competing Interest(s): Nurses' Health Study and Nurses' Health Study II were supported by research grants from the National Institutes of Health (CA172726, CA186107, CA50385, CA87969, CA49449, CA67262, CA178949). The UK Medical Research Council and Wellcome (217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. This publication is the work of the listed authors, who will serve as guarantors for the contents of this article. A comprehensive list of grants funding is available on the ALSPAC website (http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf). Funding for the collection of genotype and phenotype data used here was provided by the British Heart Foundation (SP/07/008/24066), Wellcome (WT092830M and WT08806) and UK Medical Research Council (G1001357). M.C.B., A.L.G.S. and D.A.L. work in a unit that is funded by the University of Bristol and UK Medical Research Council (MC_UU_00011/6). M.C.B.'s contribution to this work was funded by a UK Medical Research Council Skills Development Fellowship (MR/P014054/1) and D.A.L. is a National Institute of Health Research Senior Investigator (NF-0616-10102). A.L.G.S. was supported by the study of Dynamic longitudinal exposome trajectories in cardiovascular and metabolic non-communicable diseases (H2020-SC1-2019-Single-Stage-RTD, project ID 874739). The Doetinchem Cohort Study was financially supported by the Ministry of Health, Welfare and Sports of the Netherlands. The funder had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Ansh Labs performed the AMH measurements for the Doetinchem Cohort Study free of charge. Ansh Labs was not involved in the data analysis, interpretation or reporting, nor was it financially involved in any aspect of the study. R.M.G.V. was funded by the Honours Track of MSc Epidemiology, University Medical Center Utrecht with a grant from the Netherlands Organization for Scientific Research (NWO) (022.005.021). The Study of Women's Health Across the Nation (SWAN) has grant support from the National Institutes of Health (NIH), DHHS, through the National Institute on Aging (NIA), the National Institute of Nursing Research (NINR) and the NIH Office of Research on Women's Health (ORWH) (U01NR004061; U01AG012505, U01AG012535, U01AG012531, U01AG012539, U01AG012546, U01AG012553, U01AG012554, U01AG012495). The SWAN Genomic Analyses and SWAN Legacy have grant support from the NIA (U01AG017719). The Generations Study was funded by Breast Cancer Now and the Institute of Cancer Research (ICR). The ICR acknowledges NHS funding to the NIHR Biomedical Research Centre. The content of this manuscript is solely the responsibility of the authors and does not necessarily represent official views of the funders. The Sister Study was funded by the Intramural Research Program of the National Institutes of Health (NIH), National Institute of Environmental Health Sciences (Z01-ES044005 to D.P.S.); the AMH assays were supported by the Avon Foundation (02-2012-065 to H.B. Nichols and D.P.S.). The breast cancer genome-wide association analyses were supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the 'Ministère de l'Économie, de la Science et de l'Innovation du Québec' through Genome Québec and grant PSR-SIIRI-701, The National Institutes of Health (U19 CA148065, X01HG007492), Cancer Research UK (C1287/A10118, C1287/A16563, C1287/A10710) and The European Union (HEALTH-F2-2009-223175 and H2020 633784 and 634935). All studies and funders are listed in Michailidou et al. (Nature, 2017). F.J.M.B. has received fees and grant support from Merck Serono and Ferring BV. D.A.L. has received financial support from several national and international government and charitable funders as well as from Medtronic Ltd and Roche Diagnostics for research that is unrelated to this study. N.S. is scientific consultant for Ansh Laboratories. The other authors declare no competing interests., (© The Author(s) 2022. Published by Oxford University Press on behalf of European Society of Human Reproduction and Embryology.) more...
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39. Identifying molecular mediators of the relationship between body mass index and endometrial cancer risk: a Mendelian randomization analysis.
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Hazelwood E, Sanderson E, Tan VY, Ruth KS, Frayling TM, Dimou N, Gunter MJ, Dossus L, Newton C, Ryan N, Pournaras DJ, O'Mara TA, Davey Smith G, Martin RM, and Yarmolinsky J
- Subjects
- Body Mass Index, Female, Genome-Wide Association Study, Humans, Insulin, Polymorphism, Single Nucleotide genetics, Risk Factors, Testosterone, Endometrial Neoplasms epidemiology, Endometrial Neoplasms genetics, Mendelian Randomization Analysis
- Abstract
Background: Endometrial cancer is the most common gynaecological cancer in high-income countries. Elevated body mass index (BMI) is an established modifiable risk factor for this condition and is estimated to confer a larger effect on endometrial cancer risk than any other cancer site. However, the molecular mechanisms underpinning this association remain unclear. We used Mendelian randomization (MR) to evaluate the causal role of 14 molecular risk factors (hormonal, metabolic and inflammatory markers) in endometrial cancer risk. We then evaluated and quantified the potential mediating role of these molecular traits in the relationship between BMI and endometrial cancer using multivariable MR., Methods: Genetic instruments to proxy 14 molecular risk factors and BMI were constructed by identifying single-nucleotide polymorphisms (SNPs) reliably associated (P < 5.0 × 10
-8 ) with each respective risk factor in previous genome-wide association studies (GWAS). Summary statistics for the association of these SNPs with overall and subtype-specific endometrial cancer risk (12,906 cases and 108,979 controls) were obtained from a GWAS meta-analysis of the Endometrial Cancer Association Consortium (ECAC), Epidemiology of Endometrial Cancer Consortium (E2C2) and UK Biobank. SNPs were combined into multi-allelic models and odds ratios (ORs) and 95% confidence intervals (95% CIs) were generated using inverse-variance weighted random-effects models. The mediating roles of the molecular risk factors in the relationship between BMI and endometrial cancer were then estimated using multivariable MR., Results: In MR analyses, there was strong evidence that BMI (OR per standard deviation (SD) increase 1.88, 95% CI 1.69 to 2.09, P = 3.87 × 10-31 ), total testosterone (OR per inverse-normal transformed nmol/L increase 1.64, 95% CI 1.43 to 1.88, P = 1.71 × 10-12 ), bioavailable testosterone (OR per natural log transformed nmol/L increase: 1.46, 95% CI 1.29 to 1.65, P = 3.48 × 10-9 ), fasting insulin (OR per natural log transformed pmol/L increase: 3.93, 95% CI 2.29 to 6.74, P = 7.18 × 10-7 ) and sex hormone-binding globulin (SHBG, OR per inverse-normal transformed nmol/L increase 0.71, 95% CI 0.59 to 0.85, P = 2.07 × 10-4 ) had a causal effect on endometrial cancer risk. Additionally, there was suggestive evidence that total serum cholesterol (OR per mg/dL increase 0.90, 95% CI 0.81 to 1.00, P = 4.01 × 10-2 ) had an effect on endometrial cancer risk. In mediation analysis, we found evidence for a mediating role of fasting insulin (19% total effect mediated, 95% CI 5 to 34%, P = 9.17 × 10-3 ), bioavailable testosterone (15% mediated, 95% CI 10 to 20%, P = 1.43 × 10-8 ) and SHBG (7% mediated, 95% CI 1 to 12%, P = 1.81 × 10-2 ) in the relationship between BMI and endometrial cancer risk., Conclusions: Our comprehensive MR analysis provides insight into potential causal mechanisms linking BMI with endometrial cancer risk and suggests targeting of insulinemic and hormonal traits as a potential strategy for the prevention of endometrial cancer., (© 2022. The Author(s).) more...- Published
- 2022
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40. Do sex hormones confound or mediate the effect of chronotype on breast and prostate cancer? A Mendelian randomization study.
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Hayes BL, Robinson T, Kar S, Ruth KS, Tsilidis KK, Frayling T, Murray A, Martin RM, Lawlor DA, and Richmond RC
- Subjects
- Chronobiology Phenomena, Databases, Genetic, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Risk Factors, Breast Neoplasms genetics, Gonadal Steroid Hormones metabolism, Mendelian Randomization Analysis methods, Polymorphism, Single Nucleotide, Prostatic Neoplasms genetics
- Abstract
Morning-preference chronotype has been found to be protective against breast and prostate cancer. Sex hormones have been implicated in relation to chronotype and the development of both cancers. This study aimed to assess whether sex hormones confound or mediate the effect of chronotype on breast and prostate cancer using a Mendelian Randomization (MR) framework. Genetic variants associated with chronotype and sex hormones (total testosterone, bioavailable testosterone, sex hormone binding globulin, and oestradiol) (p<5×10-8) were obtained from published genome-wide association studies (n≤244,207 females and n≤205,527 males). These variants were used to investigate causal relationships with breast (nCases/nControls = 133,384/113,789) and prostate (nCases/nControls = 79,148/61,106) cancer using univariable, bidirectional and multivariable MR. In females, we found evidence for: I) Reduced risk of breast cancer per category increase in morning-preference (OR = 0.93, 95% CI:0. 88, 1.00); II) Increased risk of breast cancer per SD increase in bioavailable testosterone (OR = 1.10, 95% CI: 1.01, 1.19) and total testosterone (OR = 1.15, 95% CI:1.07, 1.23); III) Bidirectional effects between morning-preference and both bioavailable and total testosterone (e.g. mean SD difference in bioavailable testosterone = -0.08, 95% CI:-0.12, -0.05 per category increase in morning-preference vs difference in morning-preference category = -0.04, 95% CI: -0.08, 0.00 per SD increase in bioavailable testosterone). In males, we found evidence for: I) Reduced risk of prostate cancer per category increase in morning-preference (OR = 0.90, 95% CI: 0.83, 0.97) and II) Increased risk of prostate cancer per SD increase in bioavailable testosterone (OR = 1.22, 95% CI: 1.08, 1.37). No bidirectional effects were found between morning-preference and testosterone in males. While testosterone levels were causally implicated with both chronotype and cancer, there was inconsistent evidence for testosterone as a mediator of the relationship. The protective effect of morning-preference on both breast and prostate cancer is clinically interesting, although it may be difficult to effectively modify chronotype. Further studies are needed to investigate other potentially modifiable intermediates., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: DAL has received support from Roche Diagnostics and Medtronic Ltd for research unrelated to that presented here. TR has received grants from Daiichi-Sankyo and Amgen to attend educational workshops. All other authors have no competing interests to declare. more...
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- 2022
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41. Genetic insights into biological mechanisms governing human ovarian ageing.
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Ruth KS, Day FR, Hussain J, Martínez-Marchal A, Aiken CE, Azad A, Thompson DJ, Knoblochova L, Abe H, Tarry-Adkins JL, Gonzalez JM, Fontanillas P, Claringbould A, Bakker OB, Sulem P, Walters RG, Terao C, Turon S, Horikoshi M, Lin K, Onland-Moret NC, Sankar A, Hertz EPT, Timshel PN, Shukla V, Borup R, Olsen KW, Aguilera P, Ferrer-Roda M, Huang Y, Stankovic S, Timmers PRHJ, Ahearn TU, Alizadeh BZ, Naderi E, Andrulis IL, Arnold AM, Aronson KJ, Augustinsson A, Bandinelli S, Barbieri CM, Beaumont RN, Becher H, Beckmann MW, Benonisdottir S, Bergmann S, Bochud M, Boerwinkle E, Bojesen SE, Bolla MK, Boomsma DI, Bowker N, Brody JA, Broer L, Buring JE, Campbell A, Campbell H, Castelao JE, Catamo E, Chanock SJ, Chenevix-Trench G, Ciullo M, Corre T, Couch FJ, Cox A, Crisponi L, Cross SS, Cucca F, Czene K, Smith GD, de Geus EJCN, de Mutsert R, De Vivo I, Demerath EW, Dennis J, Dunning AM, Dwek M, Eriksson M, Esko T, Fasching PA, Faul JD, Ferrucci L, Franceschini N, Frayling TM, Gago-Dominguez M, Mezzavilla M, García-Closas M, Gieger C, Giles GG, Grallert H, Gudbjartsson DF, Gudnason V, Guénel P, Haiman CA, Håkansson N, Hall P, Hayward C, He C, He W, Heiss G, Høffding MK, Hopper JL, Hottenga JJ, Hu F, Hunter D, Ikram MA, Jackson RD, Joaquim MDR, John EM, Joshi PK, Karasik D, Kardia SLR, Kartsonaki C, Karlsson R, Kitahara CM, Kolcic I, Kooperberg C, Kraft P, Kurian AW, Kutalik Z, La Bianca M, LaChance G, Langenberg C, Launer LJ, Laven JSE, Lawlor DA, Le Marchand L, Li J, Lindblom A, Lindstrom S, Lindstrom T, Linet M, Liu Y, Liu S, Luan J, Mägi R, Magnusson PKE, Mangino M, Mannermaa A, Marco B, Marten J, Martin NG, Mbarek H, McKnight B, Medland SE, Meisinger C, Meitinger T, Menni C, Metspalu A, Milani L, Milne RL, Montgomery GW, Mook-Kanamori DO, Mulas A, Mulligan AM, Murray A, Nalls MA, Newman A, Noordam R, Nutile T, Nyholt DR, Olshan AF, Olsson H, Painter JN, Patel AV, Pedersen NL, Perjakova N, Peters A, Peters U, Pharoah PDP, Polasek O, Porcu E, Psaty BM, Rahman I, Rennert G, Rennert HS, Ridker PM, Ring SM, Robino A, Rose LM, Rosendaal FR, Rossouw J, Rudan I, Rueedi R, Ruggiero D, Sala CF, Saloustros E, Sandler DP, Sanna S, Sawyer EJ, Sarnowski C, Schlessinger D, Schmidt MK, Schoemaker MJ, Schraut KE, Scott C, Shekari S, Shrikhande A, Smith AV, Smith BH, Smith JA, Sorice R, Southey MC, Spector TD, Spinelli JJ, Stampfer M, Stöckl D, van Meurs JBJ, Strauch K, Styrkarsdottir U, Swerdlow AJ, Tanaka T, Teras LR, Teumer A, Þorsteinsdottir U, Timpson NJ, Toniolo D, Traglia M, Troester MA, Truong T, Tyrrell J, Uitterlinden AG, Ulivi S, Vachon CM, Vitart V, Völker U, Vollenweider P, Völzke H, Wang Q, Wareham NJ, Weinberg CR, Weir DR, Wilcox AN, van Dijk KW, Willemsen G, Wilson JF, Wolffenbuttel BHR, Wolk A, Wood AR, Zhao W, Zygmunt M, Chen Z, Li L, Franke L, Burgess S, Deelen P, Pers TH, Grøndahl ML, Andersen CY, Pujol A, Lopez-Contreras AJ, Daniel JA, Stefansson K, Chang-Claude J, van der Schouw YT, Lunetta KL, Chasman DI, Easton DF, Visser JA, Ozanne SE, Namekawa SH, Solc P, Murabito JM, Ong KK, Hoffmann ER, Murray A, Roig I, and Perry JRB more...
- Subjects
- Adult, Alleles, Animals, Bone and Bones metabolism, Checkpoint Kinase 1 genetics, Checkpoint Kinase 2 genetics, Diabetes Mellitus, Type 2, Diet, Europe ethnology, Asia, Eastern ethnology, Female, Fertility genetics, Fragile X Mental Retardation Protein genetics, Genetic Predisposition to Disease, Genome-Wide Association Study, Healthy Aging genetics, Humans, Longevity genetics, Menopause genetics, Menopause, Premature genetics, Mice, Mice, Inbred C57BL, Middle Aged, Primary Ovarian Insufficiency genetics, Uterus, Aging genetics, Ovary metabolism
- Abstract
Reproductive longevity is essential for fertility and influences healthy ageing in women
1,2 , but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations3 . The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.) more...- Published
- 2021
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42. Genome-wide association study meta-analysis identifies three novel loci for circulating anti-Müllerian hormone levels in women.
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Verdiesen RM, van der Schouw YT, van Gils CH, Verschuren WM, Broekmans FJ, Borges MC, Soares AL, Lawlor DA, Eliassen AH, Kraft P, Sandler DP, Harlow SD, Smith JA, Santoro N, Schoemaker MJ, Swerdlow AJ, Murray A, Ruth KS, and Onland-Moret NC more...
- Abstract
Anti-Müllerian hormone (AMH) is expressed by antral stage ovarian follicles in women. Consequently, circulating AMH levels are detectable until menopause. Variation in age-specific AMH levels has been associated with breast cancer and polycystic ovary syndrome (PCOS), amongst other diseases. Identification of genetic variants underlying variation in AMH levels could provide clues about the physiological mechanisms that explain these AMH-disease associations. To date, only one variant in MCM8 has been identified to be associated with circulating AMH levels in women. We aimed to identify additional variants for AMH through a GWAS meta-analysis including data from 7049 premenopausal women of European ancestry, which more than doubles the sample size of the largest previous GWAS. We identified four loci associated with AMH levels at p < 5×10
-8 : the previously reported MCM8 locus and three novel signals in or near AMH, TEX41 , and CDCA7 . The strongest signal was a missense variant in the AMH gene (rs10417628). Most prioritized genes at the other three identified loci were involved in cell cycle regulation. Genetic correlation analyses indicated a strong positive correlation among SNPs for AMH levels and for age at menopause (rg = 0.82, FDR=0.003). Exploratory Mendelian randomization analyses did not support a causal effect of AMH on breast cancer or PCOS risk, but should be interpreted with caution as they may be underpowered and the validity of genetic instruments could not be extensively explored. In conclusion, we identified a variant in the AMH gene and three other loci that may affect circulating AMH levels in women. more...- Published
- 2020
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43. Large Copy-Number Variants in UK Biobank Caused by Clonal Hematopoiesis May Confound Penetrance Estimates.
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Tuke M, Tyrrell J, Ruth KS, Beaumont RN, Wood AR, Murray A, Frayling TM, Weedon MN, and Wright CF
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- Adult, Aged, Alleles, Aneuploidy, Biological Specimen Banks, Chromosomes genetics, Female, Humans, Male, Middle Aged, Mosaicism, Mutation genetics, Penetrance, United Kingdom, DNA Copy Number Variations genetics, Hematopoiesis genetics
- Abstract
Large copy-number variants (CNVs) are strongly associated with both developmental delay and cancer, but the type of disease depends strongly on when and where the mutation occurred, i.e., germline versus somatic. We used microarray data from UK Biobank to investigate the prevalence and penetrance of large autosomal CNVs and chromosomal aneuploidies using a standard CNV detection algorithm not designed for detecting mosaic variants. We found 160 individuals that carry >10 Mb copy number changes, including 56 with whole chromosome aneuploidies. Nineteen (12%) individuals had a diagnosis of Down syndrome or other developmental disorder, while 84 (52.5%) individuals had a diagnosis of hematological malignancies or chronic myeloproliferative disorders. Notably, there was no evidence of mosaicism in the blood for many of these large CNVs, so they could easily be mistaken for germline alleles even when caused by somatic mutations. We therefore suggest that somatic mutations associated with blood cancers may result in false estimates of rare variant penetrance from population biobanks., (Copyright © 2020 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.) more...
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- 2020
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44. Using human genetics to understand the disease impacts of testosterone in men and women.
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Ruth KS, Day FR, Tyrrell J, Thompson DJ, Wood AR, Mahajan A, Beaumont RN, Wittemans L, Martin S, Busch AS, Erzurumluoglu AM, Hollis B, O'Mara TA, McCarthy MI, Langenberg C, Easton DF, Wareham NJ, Burgess S, Murray A, Ong KK, Frayling TM, and Perry JRB more...
- Subjects
- Biological Specimen Banks, Biomarkers blood, Body Composition, Breast Neoplasms blood, Breast Neoplasms genetics, Cluster Analysis, Diabetes Mellitus, Type 2 complications, Diabetes Mellitus, Type 2 genetics, Endometrial Neoplasms blood, Endometrial Neoplasms genetics, Estradiol blood, Female, Genome-Wide Association Study, Genotype, Haplotypes, Humans, Male, Mendelian Randomization Analysis, Odds Ratio, Phenotype, Polycystic Ovary Syndrome etiology, Polycystic Ovary Syndrome genetics, Polymorphism, Single Nucleotide, Prostatic Neoplasms blood, Prostatic Neoplasms genetics, Sex Factors, Software, United Kingdom, Diabetes Mellitus, Type 2 blood, Polycystic Ovary Syndrome blood, Testosterone blood, Testosterone pharmacology
- Abstract
Testosterone supplementation is commonly used for its effects on sexual function, bone health and body composition, yet its effects on disease outcomes are unknown. To better understand this, we identified genetic determinants of testosterone levels and related sex hormone traits in 425,097 UK Biobank study participants. Using 2,571 genome-wide significant associations, we demonstrate that the genetic determinants of testosterone levels are substantially different between sexes and that genetically higher testosterone is harmful for metabolic diseases in women but beneficial in men. For example, a genetically determined 1 s.d. higher testosterone increases the risks of type 2 diabetes (odds ratio (OR) = 1.37 (95% confidence interval (95% CI): 1.22-1.53)) and polycystic ovary syndrome (OR = 1.51 (95% CI: 1.33-1.72)) in women, but reduces type 2 diabetes risk in men (OR = 0.86 (95% CI: 0.76-0.98)). We also show adverse effects of higher testosterone on breast and endometrial cancers in women and prostate cancer in men. Our findings provide insights into the disease impacts of testosterone and highlight the importance of sex-specific genetic analyses. more...
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- 2020
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45. Response to Prakash et al.
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Tuke MA, Ruth KS, Wood AR, Beaumont RN, Tyrrell J, Jones SE, Yaghootkar H, Turner CLS, Donohoe ME, Brooke AM, Collinson MN, Freathy RM, Weedon MN, Frayling TM, and Murray A
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- Adult, Humans, Penetrance, Syndrome, Turner Syndrome genetics
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- 2019
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46. Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.
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Turcot V, Lu Y, Highland HM, Schurmann C, Justice AE, Fine RS, Bradfield JP, Esko T, Giri A, Graff M, Guo X, Hendricks AE, Karaderi T, Lempradl A, Locke AE, Mahajan A, Marouli E, Sivapalaratnam S, Young KL, Alfred T, Feitosa MF, Masca NGD, Manning AK, Medina-Gomez C, Mudgal P, Ng MCY, Reiner AP, Vedantam S, Willems SM, Winkler TW, Abecasis G, Aben KK, Alam DS, Alharthi SE, Allison M, Amouyel P, Asselbergs FW, Auer PL, Balkau B, Bang LE, Barroso I, Bastarache L, Benn M, Bergmann S, Bielak LF, Blüher M, Boehnke M, Boeing H, Boerwinkle E, Böger CA, Bork-Jensen J, Bots ML, Bottinger EP, Bowden DW, Brandslund I, Breen G, Brilliant MH, Broer L, Brumat M, Burt AA, Butterworth AS, Campbell PT, Cappellani S, Carey DJ, Catamo E, Caulfield MJ, Chambers JC, Chasman DI, Chen YI, Chowdhury R, Christensen C, Chu AY, Cocca M, Collins FS, Cook JP, Corley J, Galbany JC, Cox AJ, Crosslin DS, Cuellar-Partida G, D'Eustacchio A, Danesh J, Davies G, Bakker PIW, Groot MCH, Mutsert R, Deary IJ, Dedoussis G, Demerath EW, Heijer M, Hollander AI, Ruijter HM, Dennis JG, Denny JC, Di Angelantonio E, Drenos F, Du M, Dubé MP, Dunning AM, Easton DF, Edwards TL, Ellinghaus D, Ellinor PT, Elliott P, Evangelou E, Farmaki AE, Farooqi IS, Faul JD, Fauser S, Feng S, Ferrannini E, Ferrieres J, Florez JC, Ford I, Fornage M, Franco OH, Franke A, Franks PW, Friedrich N, Frikke-Schmidt R, Galesloot TE, Gan W, Gandin I, Gasparini P, Gibson J, Giedraitis V, Gjesing AP, Gordon-Larsen P, Gorski M, Grabe HJ, Grant SFA, Grarup N, Griffiths HL, Grove ML, Gudnason V, Gustafsson S, Haessler J, Hakonarson H, Hammerschlag AR, Hansen T, Harris KM, Harris TB, Hattersley AT, Have CT, Hayward C, He L, Heard-Costa NL, Heath AC, Heid IM, Helgeland Ø, Hernesniemi J, Hewitt AW, Holmen OL, Hovingh GK, Howson JMM, Hu Y, Huang PL, Huffman JE, Ikram MA, Ingelsson E, Jackson AU, Jansson JH, Jarvik GP, Jensen GB, Jia Y, Johansson S, Jørgensen ME, Jørgensen T, Jukema JW, Kahali B, Kahn RS, Kähönen M, Kamstrup PR, Kanoni S, Kaprio J, Karaleftheri M, Kardia SLR, Karpe F, Kathiresan S, Kee F, Kiemeney LA, Kim E, Kitajima H, Komulainen P, Kooner JS, Kooperberg C, Korhonen T, Kovacs P, Kuivaniemi H, Kutalik Z, Kuulasmaa K, Kuusisto J, Laakso M, Lakka TA, Lamparter D, Lange EM, Lange LA, Langenberg C, Larson EB, Lee NR, Lehtimäki T, Lewis CE, Li H, Li J, Li-Gao R, Lin H, Lin KH, Lin LA, Lin X, Lind L, Lindström J, Linneberg A, Liu CT, Liu DJ, Liu Y, Lo KS, Lophatananon A, Lotery AJ, Loukola A, Luan J, Lubitz SA, Lyytikäinen LP, Männistö S, Marenne G, Mazul AL, McCarthy MI, McKean-Cowdin R, Medland SE, Meidtner K, Milani L, Mistry V, Mitchell P, Mohlke KL, Moilanen L, Moitry M, Montgomery GW, Mook-Kanamori DO, Moore C, Mori TA, Morris AD, Morris AP, Müller-Nurasyid M, Munroe PB, Nalls MA, Narisu N, Nelson CP, Neville M, Nielsen SF, Nikus K, Njølstad PR, Nordestgaard BG, Nyholt DR, O'Connel JR, O'Donoghue ML, Loohuis LMO, Ophoff RA, Owen KR, Packard CJ, Padmanabhan S, Palmer CNA, Palmer ND, Pasterkamp G, Patel AP, Pattie A, Pedersen O, Peissig PL, Peloso GM, Pennell CE, Perola M, Perry JA, Perry JRB, Pers TH, Person TN, Peters A, Petersen ERB, Peyser PA, Pirie A, Polasek O, Polderman TJ, Puolijoki H, Raitakari OT, Rasheed A, Rauramaa R, Reilly DF, Renström F, Rheinberger M, Ridker PM, Rioux JD, Rivas MA, Roberts DJ, Robertson NR, Robino A, Rolandsson O, Rudan I, Ruth KS, Saleheen D, Salomaa V, Samani NJ, Sapkota Y, Sattar N, Schoen RE, Schreiner PJ, Schulze MB, Scott RA, Segura-Lepe MP, Shah SH, Sheu WH, Sim X, Slater AJ, Small KS, Smith AV, Southam L, Spector TD, Speliotes EK, Starr JM, Stefansson K, Steinthorsdottir V, Stirrups KE, Strauch K, Stringham HM, Stumvoll M, Sun L, Surendran P, Swift AJ, Tada H, Tansey KE, Tardif JC, Taylor KD, Teumer A, Thompson DJ, Thorleifsson G, Thorsteinsdottir U, Thuesen BH, Tönjes A, Tromp G, Trompet S, Tsafantakis E, Tuomilehto J, Tybjaerg-Hansen A, Tyrer JP, Uher R, Uitterlinden AG, Uusitupa M, Laan SW, Duijn CM, Leeuwen N, van Setten J, Vanhala M, Varbo A, Varga TV, Varma R, Edwards DRV, Vermeulen SH, Veronesi G, Vestergaard H, Vitart V, Vogt TF, Völker U, Vuckovic D, Wagenknecht LE, Walker M, Wallentin L, Wang F, Wang CA, Wang S, Wang Y, Ware EB, Wareham NJ, Warren HR, Waterworth DM, Wessel J, White HD, Willer CJ, Wilson JG, Witte DR, Wood AR, Wu Y, Yaghootkar H, Yao J, Yao P, Yerges-Armstrong LM, Young R, Zeggini E, Zhan X, Zhang W, Zhao JH, Zhao W, Zhao W, Zhou W, Zondervan KT, Rotter JI, Pospisilik JA, Rivadeneira F, Borecki IB, Deloukas P, Frayling TM, Lettre G, North KE, Lindgren CM, Hirschhorn JN, and Loos RJF more...
- Abstract
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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- 2019
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47. Using genetics to understand the causal influence of higher BMI on depression.
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Tyrrell J, Mulugeta A, Wood AR, Zhou A, Beaumont RN, Tuke MA, Jones SE, Ruth KS, Yaghootkar H, Sharp S, Thompson WD, Ji Y, Harrison J, Freathy RM, Murray A, Weedon MN, Lewis C, Frayling TM, and Hyppönen E more...
- Subjects
- Adult, Aged, Causality, Female, Humans, Male, Mendelian Randomization Analysis, Middle Aged, Obesity genetics, Obesity, Metabolically Benign epidemiology, Obesity, Metabolically Benign genetics, United Kingdom epidemiology, Body Mass Index, Depressive Disorder epidemiology, Obesity epidemiology
- Abstract
Background: Depression is more common in obese than non-obese individuals, especially in women, but the causal relationship between obesity and depression is complex and uncertain. Previous studies have used genetic variants associated with BMI to provide evidence that higher body mass index (BMI) causes depression, but have not tested whether this relationship is driven by the metabolic consequences of BMI nor for differences between men and women., Methods: We performed a Mendelian randomization study using 48 791 individuals with depression and 291 995 controls in the UK Biobank, to test for causal effects of higher BMI on depression (defined using self-report and Hospital Episode data). We used two genetic instruments, both representing higher BMI, but one with and one without its adverse metabolic consequences, in an attempt to 'uncouple' the psychological component of obesity from the metabolic consequences. We further tested causal relationships in men and women separately, and using subsets of BMI variants from known physiological pathways., Results: Higher BMI was strongly associated with higher odds of depression, especially in women. Mendelian randomization provided evidence that higher BMI partly causes depression. Using a 73-variant BMI genetic risk score, a genetically determined one standard deviation (1 SD) higher BMI (4.9 kg/m2) was associated with higher odds of depression in all individuals [odds ratio (OR): 1.18, 95% confidence interval (CI): 1.09, 1.28, P = 0.00007) and women only (OR: 1.24, 95% CI: 1.11, 1.39, P = 0.0001). Meta-analysis with 45 591 depression cases and 97 647 controls from the Psychiatric Genomics Consortium (PGC) strengthened the statistical confidence of the findings in all individuals. Similar effect size estimates were obtained using different Mendelian randomization methods, although not all reached P < 0.05. Using a metabolically favourable adiposity genetic risk score, and meta-analysing data from the UK biobank and PGC, a genetically determined 1 SD higher BMI (4.9 kg/m2) was associated with higher odds of depression in all individuals (OR: 1.26, 95% CI: 1.06, 1.50], P = 0.010), but with weaker statistical confidence., Conclusions: Higher BMI, with and without its adverse metabolic consequences, is likely to have a causal role in determining the likelihood of an individual developing depression., (© The Author(s) 2018. Published by Oxford University Press on behalf of the International Epidemiological Association.) more...
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- 2019
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48. Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors.
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Warrington NM, Beaumont RN, Horikoshi M, Day FR, Helgeland Ø, Laurin C, Bacelis J, Peng S, Hao K, Feenstra B, Wood AR, Mahajan A, Tyrrell J, Robertson NR, Rayner NW, Qiao Z, Moen GH, Vaudel M, Marsit CJ, Chen J, Nodzenski M, Schnurr TM, Zafarmand MH, Bradfield JP, Grarup N, Kooijman MN, Li-Gao R, Geller F, Ahluwalia TS, Paternoster L, Rueedi R, Huikari V, Hottenga JJ, Lyytikäinen LP, Cavadino A, Metrustry S, Cousminer DL, Wu Y, Thiering E, Wang CA, Have CT, Vilor-Tejedor N, Joshi PK, Painter JN, Ntalla I, Myhre R, Pitkänen N, van Leeuwen EM, Joro R, Lagou V, Richmond RC, Espinosa A, Barton SJ, Inskip HM, Holloway JW, Santa-Marina L, Estivill X, Ang W, Marsh JA, Reichetzeder C, Marullo L, Hocher B, Lunetta KL, Murabito JM, Relton CL, Kogevinas M, Chatzi L, Allard C, Bouchard L, Hivert MF, Zhang G, Muglia LJ, Heikkinen J, Morgen CS, van Kampen AHC, van Schaik BDC, Mentch FD, Langenberg C, Luan J, Scott RA, Zhao JH, Hemani G, Ring SM, Bennett AJ, Gaulton KJ, Fernandez-Tajes J, van Zuydam NR, Medina-Gomez C, de Haan HG, Rosendaal FR, Kutalik Z, Marques-Vidal P, Das S, Willemsen G, Mbarek H, Müller-Nurasyid M, Standl M, Appel EVR, Fonvig CE, Trier C, van Beijsterveldt CEM, Murcia M, Bustamante M, Bonas-Guarch S, Hougaard DM, Mercader JM, Linneberg A, Schraut KE, Lind PA, Medland SE, Shields BM, Knight BA, Chai JF, Panoutsopoulou K, Bartels M, Sánchez F, Stokholm J, Torrents D, Vinding RK, Willems SM, Atalay M, Chawes BL, Kovacs P, Prokopenko I, Tuke MA, Yaghootkar H, Ruth KS, Jones SE, Loh PR, Murray A, Weedon MN, Tönjes A, Stumvoll M, Michaelsen KF, Eloranta AM, Lakka TA, van Duijn CM, Kiess W, Körner A, Niinikoski H, Pahkala K, Raitakari OT, Jacobsson B, Zeggini E, Dedoussis GV, Teo YY, Saw SM, Montgomery GW, Campbell H, Wilson JF, Vrijkotte TGM, Vrijheid M, de Geus EJCN, Hayes MG, Kadarmideen HN, Holm JC, Beilin LJ, Pennell CE, Heinrich J, Adair LS, Borja JB, Mohlke KL, Eriksson JG, Widén EE, Hattersley AT, Spector TD, Kähönen M, Viikari JS, Lehtimäki T, Boomsma DI, Sebert S, Vollenweider P, Sørensen TIA, Bisgaard H, Bønnelykke K, Murray JC, Melbye M, Nohr EA, Mook-Kanamori DO, Rivadeneira F, Hofman A, Felix JF, Jaddoe VWV, Hansen T, Pisinger C, Vaag AA, Pedersen O, Uitterlinden AG, Järvelin MR, Power C, Hyppönen E, Scholtens DM, Lowe WL Jr, Davey Smith G, Timpson NJ, Morris AP, Wareham NJ, Hakonarson H, Grant SFA, Frayling TM, Lawlor DA, Njølstad PR, Johansson S, Ong KK, McCarthy MI, Perry JRB, Evans DM, and Freathy RM more...
- Subjects
- Adult, Blood Pressure genetics, Body Height genetics, Diabetes Mellitus, Type 2 etiology, Diabetes Mellitus, Type 2 genetics, Female, Fetal Development genetics, Genetic Predisposition to Disease, Genome-Wide Association Study, Heart Diseases etiology, Heart Diseases genetics, Humans, Infant, Newborn, Male, Maternal Inheritance genetics, Maternal-Fetal Exchange genetics, Metabolic Diseases etiology, Metabolic Diseases genetics, Models, Genetic, Polymorphism, Single Nucleotide, Pregnancy, Risk Factors, Birth Weight genetics
- Abstract
Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming. more...
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- 2019
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49. Genome-wide association study of anti-Müllerian hormone levels in pre-menopausal women of late reproductive age and relationship with genetic determinants of reproductive lifespan.
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Ruth KS, Soares ALG, Borges MC, Eliassen AH, Hankinson SE, Jones ME, Kraft P, Nichols HB, Sandler DP, Schoemaker MJ, Taylor JA, Zeleniuch-Jacquotte A, Lawlor DA, Swerdlow AJ, and Murray A
- Subjects
- Adult, Age Factors, Anti-Mullerian Hormone blood, Anti-Mullerian Hormone physiology, Base Sequence, Female, Gene Expression, Gene Expression Regulation genetics, Genetic Association Studies methods, Genetic Variation genetics, Genome-Wide Association Study methods, Haplotypes, Humans, Longevity, Menarche genetics, Middle Aged, Mitochondria genetics, Ovarian Follicle, Ovary, Polymorphism, Single Nucleotide genetics, Premenopause genetics, Reproduction genetics, Sequence Analysis, DNA, Transcriptome genetics, Anti-Mullerian Hormone genetics, Premenopause physiology
- Abstract
Anti-Müllerian hormone (AMH) is required for sexual differentiation in the fetus, and in adult females AMH is produced by growing ovarian follicles. Consequently, AMH levels are correlated with ovarian reserve, declining towards menopause when the oocyte pool is exhausted. A previous genome-wide association study identified three genetic variants in and around the AMH gene that explained 25% of variation in AMH levels in adolescent males but did not identify any genetic associations reaching genome-wide significance in adolescent females. To explore the role of genetic variation in determining AMH levels in women of late reproductive age, we carried out a genome-wide meta-analysis in 3344 pre-menopausal women from five cohorts (median age 44-48 years at blood draw). A single genetic variant, rs16991615, previously associated with age at menopause, reached genome-wide significance at P = 3.48 × 10-10, with a per allele difference in age-adjusted inverse normal AMH of 0.26 standard deviations (SD) (95% confidence interval (CI) [0.18,0.34]). We investigated whether genetic determinants of female reproductive lifespan were more generally associated with pre-menopausal AMH levels. Genetically-predicted age at menarche had no robust association but genetically-predicted age at menopause was associated with lower AMH levels by 0.18 SD (95% CI [0.14,0.21]) in age-adjusted inverse normal AMH per one-year earlier age at menopause. Our findings provide genetic support for the well-established use of AMH as a marker of ovarian reserve., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.) more...
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- 2019
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50. Genetic studies of accelerometer-based sleep measures yield new insights into human sleep behaviour.
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Jones SE, van Hees VT, Mazzotti DR, Marques-Vidal P, Sabia S, van der Spek A, Dashti HS, Engmann J, Kocevska D, Tyrrell J, Beaumont RN, Hillsdon M, Ruth KS, Tuke MA, Yaghootkar H, Sharp SA, Ji Y, Harrison JW, Freathy RM, Murray A, Luik AI, Amin N, Lane JM, Saxena R, Rutter MK, Tiemeier H, Kutalik Z, Kumari M, Frayling TM, Weedon MN, Gehrman PR, and Wood AR more...
- Subjects
- Accelerometry methods, Circadian Rhythm, Humans, Polymorphism, Single Nucleotide, Serotonin genetics, Serotonin metabolism, Sleep Wake Disorders diagnosis, Waist-Hip Ratio, Polysomnography methods, Sleep genetics, Sleep Wake Disorders genetics
- Abstract
Sleep is an essential human function but its regulation is poorly understood. Using accelerometer data from 85,670 UK Biobank participants, we perform a genome-wide association study of 8 derived sleep traits representing sleep quality, quantity and timing, and validate our findings in 5,819 individuals. We identify 47 genetic associations at P < 5 × 10
-8 , of which 20 reach a stricter threshold of P < 8 × 10-10 . These include 26 novel associations with measures of sleep quality and 10 with nocturnal sleep duration. The majority of identified variants associate with a single sleep trait, except for variants previously associated with restless legs syndrome. For sleep duration we identify a missense variant (p.Tyr727Cys) in PDE11A as the likely causal variant. As a group, sleep quality loci are enriched for serotonin processing genes. Although accelerometer-derived measures of sleep are imperfect and may be affected by restless legs syndrome, these findings provide new biological insights into sleep compared to previous efforts based on self-report sleep measures. more...- Published
- 2019
- Full Text
- View/download PDF
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